Seasonal Crop Evapotranspiration Research Articles

Water use of Guinea grass as affected by rainfed local conditions and practices in Sub-Saharan Africa

Ongoing efforts are currently being made to rehabilitate drought-affected pastures in Sub-Saharan Africa. One approach being explored is the introduction of non-native grass species, such as Megathyrsus maximus (Guinea grass). This study aims to investigate the water use of Guinea grass in semi-arid environments under rainfed conditions. Additionally, it aims to a better understanding of the variability of water use in Guinea grass through the utilization of the Bagging machine learning algorithm. Split-plot field experiments were carried out over two consecutive rainy seasons (2020-2021). The treatments included two in-situ rainwater harvesting practices, RWH (ridging plus terracing and terracing alone), three seeding rates, SR (1.5, 2.5, and 3.5 kg ha-1), and two soil nitrogen fertilization rates, SF (95 kg N ha-1 and 0 kg N ha-1). These treatments were compared to a control plot that involved zero-tillage, no fertilization, and no rainwater harvesting. The collected datasets were analyzed using R, SPSS 15, and spreadsheets. The results showed significant differences in plant indices and soil moisture content among the treatments. However, the treatments had insignificant effects on seasonal actual crop evapotranspiration (ETa), which ranged from 1.93 to 3.29 mm day-1. The interactions between SR and RWH were found to have significant impacts on water use. The Bagging algorithm revealed that the variability in ETa could be attributed to SR (42%), RWH (31%), and SF (26%), respectively. The implementation of rainwater harvesting practices resulted in a significant reduction in water usage, saving 86% of the green water used with a water footprint of 0.25 m3 kg-1, compared to 1.7 m3 kg-1 for no adoption of RWH conditions. The water use of rainfed Guinea grass was also found highly sensitive to dry spells. Further detailed studies using multiple-layer models are recommended to gain a better understanding of the non-linear interactions in semi-arid environments.

Quinoa growth and yield, soil water dynamics, root growth, and water use indicators in response to deficit irrigation and planting methods

To address the growing issue of scarce water in the arid and semi-arid areas, it is essential to investigate the potential of drought tolerant crops and implement promising farm management strategies to improve water productivity and yield production. Therefore, a split plot experiment to investigate how different irrigation levels (I-1:100% water requirement (WR), I-2:75%WR, and I-3: 50%WR) and planting methods (P-1: basin, P-2: on-ridge, and, P-3: in-furrow) interact and affect quinoa water use, yield, root growth, and water productivity in southern Iran over two growing seasons. The results showed high seasonal crop evapotranspiration (993–1030 mm) in I-1 as a result of the high advection ratio (α), which ranged from 1.02 to 1.46 from the early vegetative to the seed filling stages. The P-3 increased transpiration rate by 4.5% and 7.7%, and decreased soil evaporation by 17% and 29% compared to P-1 and P-2, respectively. Single (Kc) and dual (Kcb + Ke) crop coefficients varied between 0.41 and 1.38 over the two growing seasons. Grain yield in P-3 were 25%, 34%, and 44% higher compared to P-1 and P-2 under I-1, I-2 and I-3, respectively. The study revealed that nearly 67% and 80% of the total root dry matter was in the 0–30 cm and 0–60 cm of the soil profile in all experimental treatments, respectively. Regardless of irrigation treatment, root length density (RLD) and root mass density (RMD) were found to be 18.9% and 15.7% lower in P-1’s top 0–20 cm of the soil profile than those obtained in P-2 and P-3, respectively. Analyses showed that the increased root length in deeper soil layers contributed to higher soil water uptake, and consequently higher crop water productivity. In addition, root-to-shoot ratio increased as the amount of the applied irrigation water was decreased. Quinoa exhibited the highest acclimation to water stress in P-3 based on water stress sensitivity coefficients (λi) and yield response factor (Ky) values. Crop water productivity (WPC) and irrigation water productivity (WPI) for grain yield varied between 0.17 and 0.28 kg m−3. In conclusion, in terms of grain yield, shoot and root dry matter and water productivity, I-2 and P-3 (75% WR irrigation level and in-furrow planting method treatment) is recommended as the optimum water and planting management strategy for quinoa cultivation in the study area as a measure to address water scarcity and food sustainability. Still, to improve yield and irrigation water efficiency, the effect of soil management practices such as mulching and organic amendments on soil water retention and nutrient availability for quinoa should be investigated.

Physiological Characteristics, Crop Growth and Grain Yield of Twelve Wheat Varieties Cultivated in the North China Plain

Climate change and water resource shortages have become important problems limiting winter wheat production in the North China Plain (NCP). Understanding the physiological characteristics of different wheat varieties and their relationship with crop growth and yield is of great importance for addressing climate change through a scientific approach, adopting reliable wheat varieties, and ensuring food production. This study was conducted throughout three winter wheat seasons from 2018 to 2021. The crop growth, physiological indicators, crop yields, and water productivity (WP) of 12 wheat varieties widely cultivated in the NCP were measured to investigate the relationships between physiological characteristics and crop yield. The results showed that among the three wheat seasons, the maximum plant height of each wheat variety was relatively stable, while the changes in maximum plant density (PDm), maximum leaf area index (LAIm), and maximum dry matter (DMm) were highly variable. The gas exchange parameters and fluorescence parameters of wheat flag leaves varied with growth stage, and certain varieties were sensitive to water stress. The wheat grain yield, seasonal crop evapotranspiration (ETa), and WP of the 12 varieties were similar in the 2019–2020 and 2020–2011 seasons and were approximately 25%, 7%, and 19% higher than those in the 2018–2019 season, respectively, in which there were consecutive cool events in the winter and spring. Generally, the grain yields were positively correlated with PDm, LAIm, DMm, ETa, the harvest index, and WP, at a significance level of 0.01. The high-yield wheat varieties had higher photosynthetic rates in the middle and late grain-filling stages. Based on these relationships, high-yield wheat varieties may be selected to address climate change in the NCP as well as other regions in the world. Considering the variations in yield and WP in the three different climatic conditions, we recommend Yingbo700, Lunxuan103, Shimai26, Shinong086, Han6172, and Hanong1412 as high-yield and drought-resistant wheat varieties to be used in the NCP.

Effects of full and deficit irrigation on the growth and quality of cool-season turfgrasses under subsurface drip irrigation

Irrigation is necessary in terms of achieving high-quality turfgrass. However, it is evident that more efficient and cost effective irrigation methods should be adapted for the sake of water conservation strategies since water consumption is high during turf irrigation. The objective of this study is to determine the effects of full and deficit irrigation with subsurface drip irrigation on growth and quality of perennial ryegrass (Lolium perenne L.) and tall fescue (Festuca arundinaceae Schreb) in a sub-humid climate of Turkey. Three irrigation treatments [I1 (full irrigation), I2 (mild water deficit, 75%), and I3 (moderate water deficit, 50%) were applied to the plants. Turf color and quality of each plot were rated visually, and clipping yields were collected. The amount of irrigation applied varied between 457.3 - 833.9 mm and 356.7 - 710.1 mm and seasonal crop evapotranspiration (ETa) values ranged from 578.4 to 1053.0 mm for tall fescue and 551.2 to 1044.0 mm for perennial ryegrass in 2018 and 2019, respectively. Among the species, tall fescue showed higher visual color, quality ratings and clipping yields. In cases where it does not matter for one or two weeks to be below the acceptable quality (<6) minimum annual irrigation amounts required to maintain quality was 689.1 mm for perennial ryegrass and 578.4 for tall fescue. The results have suggested that acceptable visual color and quality are sustainable in the tall fescue with mild water deficit application in regions where irrigation water is limited in sub-humid climates. Studies on water-saving strategies to turfgrass in regions where the climates varies from year to year are lacking in literature.

Evaluating the Impact of Future Seasonal Climate Extremes on Crop Evapotranspiration of Maize in Western Kansas Using a Machine Learning Approach

Data-driven technologies are employed in agriculture to optimize the use of limited resources. Crop evapotranspiration (ET) estimates the actual amount of water that crops require at different growth stages, thereby proving to be the essential information needed for precision irrigation. Crop ET is essential in areas like the US High Plains, where farmers rely on groundwater for irrigation. The sustainability of irrigated agriculture in the region is threatened by diminishing groundwater levels, and the increasing frequency of extreme events caused by climate change further exacerbates the situation. These conditions can significantly affect crop ET rates, leading to water stress, which adversely affects crop yields. In this study, we analyze historical climate data using a machine learning model to determine which of the climate extreme indices most influences crop ET. Crop ET is estimated using reference ET derived from the FAO Penman–Monteith equation, which is multiplied with the crop coefficient data estimated from the remotely sensed normalized difference vegetation index (NDVI). We found that the climate extreme indices of consecutive dry days and the mean weekly maximum temperatures most influenced crop ET. It was found that temperature-derived indices influenced crop ET more than precipitation-derived indices. Under the future climate scenarios, we predict that crop ET will increase by 0.4% and 1.7% in the near term, by 3.1% and 5.9% in the middle term, and by 3.8% and 9.6% at the end of the century under low greenhouse gas emission and high greenhouse gas emission scenarios, respectively. These predicted changes in seasonal crop ET can help agricultural producers to make well-informed decisions to optimize groundwater resources.

Farklı Sulama Aralıkları ve Düzeylerinin Salçalık Domatesin Verim ve Kalite Bileşenlerine Etkileri ve Ekonomik Analizi

This study was carried out to determine the effects of different irrigation intervals (II) and irrigation levels (IL) on yield, quality and net income values of processing tomato cultivation in a sub-humid climatic zone in 2019. A split-plot randomized complete block design with three replicates was used for the field experiments. The II4-days (A) and 8-days (B) were determined as main-plot factor and different IL were established according to 100% (T1), 80% (T2) and 60% (T3) of the cumulative evaporation occurring in the Class A pan were determined as the sub-plot factor. Seasonal crop evapotranspiration (ET) values varied between 419 and 527 mm. The effects of different irrigation strategies on fruit yield, average fruit weight, brix and water productivity values of processing tomato were significant at the p&amp;lt;0.01 level. The greatest fruit yield was obtained in AT1 treatment with 111.65 t ha-1. The highest water and irrigation water productivity values were obtained from AT2 as 22.4 kg m-3 and 31.4 kg m-3 and the lowest values from BT3 treatment as 16.1 kg m-3 and 26.0 kg m-3 respectively. The yield response factor (ky) was determined as 1.7 for the growing season. The net income values of different treatments ranged from 213.49 to 5557.54 $ ha-1 and the net income increased with the augmentation inthe irrigation water applied. Based on the study results, AT1 treatment was recommended to obtain maximum fruit yield and net income. However, in locations with limited water resources, AT2 treatment which provides a reasonable balance between quality components and water requirements can also be evaluated.

Evapotranspiration and Crop Coefficient of Sorghum (Sorghum bicolor L.) at Melkassa Farmland, Semi-Arid Area of Ethiopia

Sorghum has an enormous role in the economy of sorghum-growing nations. Supplying a precise amount of water to a crop based on crop needs is the main agenda in implementing water-saving agriculture. Non-weighing type lysimeters were used to determine actual crop evapotranspiration and crop coefficient of sorghum at the experimental farm of Melkassa Agricultural Research Center situated in the semi-arid area of Ethiopia. Soil-water balance approaches were applied to obtain actual crop evapotranspiration, while the Penman-Monteith technique was used to determine reference evapotranspiration. Growth stages-wise crop coefficient was computed as a ratio of actual crop evapotranspiration to reference evapotranspiration. The total seasonal sorghum actual crop evapotranspiration during the 2017 and 2018 experimental years was 358.6 and 377.54 mm, respectively. The 2 years average sorghum actual crop evapotranspiration was 368.07 mm. The mean locally developed actual crop coefficient values of 0.55, 1.15, and 0.59 were observed for the initial, mid, and end-season, respectively. The FAO-adjusted crop coefficient values for mid and end-season were 1.01 and 0.52, respectively. The developed Kc values considerably differed from the FAO-adjusted Kc values. So, the determination of actual crop evapotranspiration and crop coefficient for crop growth at local climate conditions is vital for decision-making concerning water management in the area where irrigation is practiced.

Effects of Salinity Stress on Drip-Irrigated Tomatoes Grown under Mediterranean-Type Greenhouse Conditions

Plant tolerance to salinity stress is vital for irrigation scheduling, decision-making, planning and operation, and water resource management. This study is aimed to investigate the effects of irrigation water salinity on water use, growth, physiology, and yield parameters of drip-irrigated tomatoes in two different growing seasons. In addition to control (0.7 dS m−1), three irrigation water salinity levels: 2.5 (low), 5.0 (moderate), and 7.5 (high) dS m−1 were used. In both seasons, autumn 2021 and spring 2022, increased water salinities caused an increase in soil salinity, while a decrease in seasonal crop evapotranspiration. Plant heights did not show significant differences under different salinity levels in autumn 2021, while a meaningful difference among treatments was found in spring 2022. Marketable and total tomato yields, and the leaf area index showed significant decreases under increased salinities in both seasons. Stomatal conductance was not affected by salinity levels. The salt tolerance models for marketable and total fruit yields showed a low threshold and slope value in autumn 2021, contrasting with a high threshold and slope value determined in spring 2022. The results suggest that the salinity slope value should be considered, as well as the salinity threshold value, for decision making in tomato production at different growing seasons.

Crop response to thermal stress without yield loss in irrigated maize and soybean in Nebraska

Thermal sensing provides rapid and accurate estimation of crop water stress through canopy temperature data. Canopy temperature is highly dependent on the transpiration rate of the leaves. It is usually assumed that any reduction in crop evapotranspiration (ET) leads to crop yield loss. As a result, an increase in canopy temperature due to a decrease in crop ET would indicate crop yield loss. This research evaluated the hypothesis that crop water stress could be detected using canopy temperature measurements (increased leaf temperature) from infrared thermometers (IRTs) before incurring crop yield loss. This would be possible in a narrow range when the photosynthesis rate (and carbon assimilation) is limited by solar radiation (energy-limiting water stress) while the leaf has abundant carbon dioxide for photosynthesis. Once photosynthesis becomes limited by carbon dioxide (carbon-dioxide-limiting water stress), then yield reduction would occur. In this field experiment, measured response variables included the integrated crop water stress index (iCWSI), ET, and crop yield for maize and soybean during the 2020 and 2021 growing seasons. The irrigation was applied at four different refill levels: rainfed (0%), deficit (50%), full (100%), and over (150%). The irrigation depth was prescribed using four different irrigation methods. The field was irrigated with a center pivot irrigation system, which was also used as a platform to mount IRT sensors. The iCWSI thresholds required for irrigation management were determined using the iCWSI dataset collected in 2020. The low, medium, and high iCWSI thresholds were 120, 150, and 180, respectively for maize and 110, 130, and 150, respectively for soybean. These thresholds should be updated with iCWSI data from future studies in this region to increase the credibility of the thresholds for irrigation management. The mean iCWSI values for consecutive days after a wetting event substantially increased with time for each irrigation level and a larger range in iCWSI values was observed among the irrigation levels after three days from a wetting event. The seasonal iCWSI for different levels were found to be negatively correlated with seasonal evapotranspiration for both years. The correlations between seasonal ET and crop yield were significant with the rainfed and deficit levels for maize (p-value < 0.001) and soybean (p-value = 0.04) in 2020. The iCWSI and yield data for the fully watered plots indicated that thermal stress was detected using the sensing system without incurring yield loss (i.e., energy-limiting water stress). The ET and yield data for 2021 indicated that reduction in seasonal crop ET did not result in yield loss which also supported the hypothesis. Future studies should investigate whether this phenomenon of detecting crop water stress in an early stage without yield loss is observed in other climates and locations.

Water productivity of forage sorghum in response to winter cover crops in semi-arid irrigated conditions

Forage sorghum (Sorghum bicolor (L.) Moench) is a suitable alternative for corn silage in water-limited environments due to its similar yield potential as corn but with less water input. Cover cropping could further improve forage sorghum yield and water productivity, making it the best alternative forage crop for arid and semi-arid regions. This two-year study evaluated the effect of fallow and cover crops on soil volumetric water content (VWC), soil water extraction, changes in soil water storage (∆S), seasonal crop evapotranspiration (ETseasonal), cropping system evapotranspiration (ETsystem), seasonal crop water productivity (CWPseasonal), cropping system water productivity (CWPsystem) and forage sorghum yield under a no-till semi-arid irrigated condition. Treatments included three winter cover crop mixtures: grasses + brassicas + legumes (GBL), grasses + brassicas (GB), grasses + legumes (GL), and a no-cover crop control (fallow), arranged in a randomized complete block design with four replications. Cover crops significantly reduced soil VWC at the beginning and up to 30 days after sorghum planting (DAP). However, at 60 DAP, the VWC was mostly similar among all treatments, and at 90 DAP, it was 17–21% higher under the cover crop treatments than fallow. The ETseasonal was 22–26% higher under cover crops than fallow during cover crop growth, but it was 12–13% greater under fallow than the cover crops during forage sorghum growth. Total soil water extraction at sorghum harvest was 8–89% higher under fallow than cover crops treatments. Averaged across years, cover crop biomass yield was 11% greater with the GBL mixture than the GB and GL mixtures. Forage sorghum yield was 23%, 32%, and 18% higher under GBL, GB, and GL cover crop mixtures, respectively, than fallow. Compared to fallow, cover crop mixtures improved sorghum CWP by 38–43%. Results indicated that forage sorghum yield and CWP under semi-arid irrigated systems could be substantially improved with winter cover cropping than leaving the land fallow.

Evaluation of Aqua-Crop Model using Onion Crop under Deficit Irrigation and Mulch in Semi-arid Nigeria

The Aqua-Crop simulation model has been playing a crucial role in assessing the performance of the existing strategies for the management of irrigation schemes for improving agricultural water use efficiency. This study evaluated the Aqua-Crop model using Onion crops under deficit irrigation and mulch practices in semi-arid Nigeria. Measurements were taken from the experimental plots which consisted of irrigation and mulch each at 4 levels were used to evaluate the Aqua-Crop model using canopy cover, biomass, yield, actual crop ET, and water productivity of Onion during the 2021 irrigation season. The simulated results from the Aqua-Crop model were evaluated and statistically compared with the experimental results. The model simulated canopy cover with the highest degree of correlation coefficient (0.74 ≤ r ≤ 0.94). The model perfectly predicted Onion yield and biomass under full irrigation irrespective of the mulching. However, the model underestimated Onion yield and biomass at deficit irrigation. The model has perfectly estimated the seasonal actual crop evapotranspiration at different irrigation levels and mulch materials while underestimating water productivity in most of the treatments except at 100% irrigation under white synthetic mulch. However, both model and experimental water productivity were better at white synthetic mulch plots. Therefore, the Aqua-Crop model has proven to be a good Onion crop growth and yield predictor under different irrigation levels and mulch materials which can help improve Onion productivity in water-stressed areas like semi-arid Nigeria.

Proposing a combined method for the estimation of spatial and temporal variation of crop water productivity under deficit irrigation scenarios based on the AquaCrop model

Deficit irrigation is a management strategy to improve crop water productivity, especially in arid and semi-arid regions. Soil characteristics and weather parameters are among the factors affecting crop water productivity in water stress conditions. Due to spatial changes in soil characteristics and temporal and spatial variations in meteorological parameters, it can be expected that crop water productivity will also have temporal and spatial variations. In this study, by combining the Geographic Information System (GIS) with the grid weather generation tools from the Crop Growth Monitoring System (CGMS) and the plug-in version of the AquaCrop, a combined method was developed to investigate the spatial and temporal variation of crop yield, seasonal crop evapotranspiration, and water productivity of maize under various irrigation scenarios. The proposed model was implemented in a case study in the west of Iran. The study area was divided into 37 grid weather with 5 * 5 km and 19 soil units. By overlaying soil units and grid weathers, 94 homogeneous units were created. The model was executed for 94 homogeneous areas, using calibrated crop file of grain maize under four irrigation scenarios of 40, 60, 80, and 100% of potential irrigation requirement (S40, S60, S80, and S100, respectively) for 28 years (1988–2015) of weather data (10,528 runs). The results showed that by increasing water stress, the percentage of spatial and temporal variation of the studied parameters (crop yield, seasonal crop water requirement, and water productivity) would be increased. The percentage of spatial changes in crop yield and crop water productivity was more significant than temporal changes. The average of crop water productivity in the scenarios of S100, S80, S60, and S40 was determined as 1.5, 1.4, 1.2, and 0.5 kg m−3, respectively.

Effects of Supplementary Irrigation and Nitrogen Fertilization on Characteristics of Sun Cured Tobacco in Semi-Arid Conditions

ABSTRACT Nitrogen and water should be applied at the right time and amount to obtain optimum crop yield in arid and semi-arid regions. The study was carried out in 2017–2018 to investigate the effects of different supplementary irrigation levels applied after harvests, and different nitrogen sources on water use efficiency (WUE), yield and quality characteristics of sun-cured tobacco. The study included five different nitrogen sources (N1: zero-nitrogen, N2: ammonium nitrate, N3: ammonium sulfate, N4: calcium ammonium nitrate, and N5: urea) and four different irrigation treatments (I0:No irrigation; I33:66% deficit, I66:33% deficit and I100:100% full irrigation). The effects of nitrogen sources and supplementary irrigation treatments on plant height, leaf number, leaf width, leaf height, yield, quality grade, sugars, nicotine, phenolics, WUE and irrigation water use efficiency (IWUE) were statistically significant. Seasonal crop evapotranspiration values ranged between 117.7 and 235.3 mm. The highest WUE 1.65 kg m−3 and IWUE: 10.48 kg m−3 were recorded in I33 treatment. Plant characteristics were different between nitrogen sources; however, the results did not indicate a prominent nitrogen form. The results for supplementary irrigation revealed that the I100 treatment in semi-arid conditions increased the sun-cured tobacco yield by 22% with acceptable quality improvements. The gross income increased 1705 $ ha−1 with the increase in tobacco yield and sale price per hectare.

Evaluation of Factors Driving Post-Harvest Losses among Arable Crop Farmers in Ogbomoso, Oyo State, Nigeria

The development of crop coefficients (KC), the ratio of crop evapotranspiration (ETc) to reference evapotranspiration (ETo) is important for estimating irrigation water requirements in relation to specific crop phenological development. This research was conducted to determine growth-stage-specific Kc and crop water use for onion at Werer Agricultural Research Center, Middle Awash Valley Ethiopia during the main season (July–October) and during cool cropping seasons (March–June) from 2012-2015. Three non weighing lysimeters of 1.6 m x 1.6 m in surface area and 2 m deep were used to measure crop water use and local weather data were used to determine the reference evapotranspiration (ETo). The results showed that the obtained Kc values for main cropping season planted onion during initial, crop development, mid season and late-season stages were 0.57, 0.78, 1.03 and 0.77 respectively. Meanwhile, the corresponding Kc values for cool cropping season planted onion were 0.49, 0.90, 1.01, and 0.79 in the respective growth stages. The seasonal crop evapotranspiration was 525.83mm and 465.57mm during main and cool cropping season respectively. The measured Kc values were significantly different from the FAO-56 reported values. Therefore, local calibration of crop coefficients is an essential for efficient irrigation water management and precise water applications. Keywords: onion, crop coefficient, growth stages, water balance, evapotranspiration, lysimeter DOI: 10.7176/JNSR/13-6-01 Publication date: March 31 st 2021

Response of maize hybrids under limited irrigation capacities: Crop water use

AbstractMaize (Zea mays L.) production in the semiarid Texas High Plains (THP) often suffers exceptional yield reductions when irrigation cannot meet seasonal and peak water requirements. Drought‐tolerant hybrids may reduce yield losses resulting from water stress by altering seasonal soil water use patterns to permit greater uptake during yield‐sensitive growth stages. We examined the effect of irrigation capacity (8.47 and 4.23 mm d−1) and planting rates (74,000 and 95,000 seeds ha−1) during three growing seasons (2016–2018) on water use of three maize hybrids, two of which were considered drought tolerant. Changes in stored soil water were examined for the entire profile and for segregated depth increments (0–0.4, 0.4–0.8, and 0.8–1.4 m). Seasonal crop evapotranspiration averaged 754 and 592 mm across years for the high and low irrigation capacities, respectively. Irrigation level significantly affected seasonal change in stored soil water in 1 yr (2018) with greater depletion at harvest under the low irrigation capacity. Soil water use at 0.8–1.4 m comprised &lt;4% of seasonal water use. Hybrids did not differ with respect to growing season crop water use. Stored soil water throughout the growing season within the examined depth increments were similar among hybrids and plant densities, with significant differences occurring infrequently and being inconsistent across years. Drought‐tolerant traits may have a diminished effect on transpiration in this study because of the dense soil‐limiting root proliferation or the high atmospheric demand at the study location.

Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting

Abstract. Evapotranspiration plays an important role in the terrestrial water cycle. Reference crop evapotranspiration (ETo) has been widely used to estimate water transfer from vegetation surface to the atmosphere. Seasonal ETo forecasting provides valuable information for effective water resource management and planning. Climate forecasts from general circulation models (GCMs) have been increasingly used to produce seasonal ETo forecasts. Statistical calibration plays a critical role in correcting bias and dispersion errors in GCM-based ETo forecasts. However, time-dependent errors resulting from GCM misrepresentations of climate trends have not been explicitly corrected in ETo forecast calibrations. We hypothesize that reconstructing climate trends through statistical calibration will add extra skills to seasonal ETo forecasts. To test this hypothesis, we calibrate raw seasonal ETo forecasts constructed with climate forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) SEAS5 model across Australia, using the recently developed Bayesian joint probability trend-aware (BJP-ti) model. Raw ETo forecasts demonstrate significant inconsistencies with observations in both magnitudes and spatial patterns of temporal trends, particularly at long lead times. The BJP-ti model effectively corrects misrepresented trends and reconstructs the observed trends in calibrated forecasts. Improving trends through statistical calibration increases the correlation coefficient between calibrated forecasts and observations (r) by up to 0.25 and improves the continuous ranked probability score (CRPS) skill score by up to 15 (%) in regions where climate trends are misrepresented by raw forecasts. Skillful ETo forecasts produced in this study could be used for streamflow forecasting, modeling of soil moisture dynamics, and irrigation water management. This investigation confirms the necessity of reconstructing climate trends in GCM-based seasonal ETo forecasting and provides an effective tool for addressing this need. We anticipate that future GCM-based seasonal ETo forecasting will benefit from correcting time-dependent errors through trend reconstruction.

Simulation of wheat yield using CERES-Wheat under rainfed and supplemental irrigation conditions in a semi-arid environment

Wheat-fallow rotation is the major land-use system in the rainfed cropping system of Pakistan. Crop production in rainfed cropping systems is often jeopardized due to the scare and erratic seasonal patterns of rainfall. Climate change is further threatening the extent and productivity of rainfed agriculture in Pakistan. Climatic risk reduction strategies such as supplemental irrigation (SI) can assist in sustaining the productivity of rainfed agriculture. However, little has been done to investigate the potential of SI in sustaining the productivity of the rainfed cropping system of Pakistan despite the recent water resource developments in the rainfed regions of the country. For this purpose, a four-year (2010–2014) study was conducted to assess wheat yield and water productivity under rainfed and SI using a crop modeling approach. Calibrated CERES-Wheat was evaluated for its ability to simulate soil moisture dynamics, water productivity, canopy growth, in-season biomass, phenology, grain yield, and biomass at harvest based on soil water balance. Results showed a good to excellent performance of CERES-Wheat during evaluation. For example, combined values of soil moisture content between different layers, root zone soil moisture, seasonal crop evapotranspiration, in-season biomass growth, and canopy cover showed NRMSE values ranging from 13%–89%, 5–11%, 2–17%, 12–26%, and 13–22%, respectively. The NRMSE values of rainfall productivity of biomass and grain yield and water productivity of biomass and grain yield ranged from 18%, 16%, and 17%, 6%, respectively. The model was also applied to determine favorable management practices (appropriate planting dates from 15 October to 15 December at 15-day intervals and SI of 50 mm either at planting or 30 days after planting) as their determination under actual field conditions is laborious. Simulations for the best combination of planting date and SI suggested that higher crop yield and water productivity can be achieved with planting in November with irrigation applied 30 days after planting.

Modeling the Effect of Planting Dates and Nitrogen Application Rates on Potatoes Water Productivity in Jordan Valley

Agricultural sector in Jordan is facing serious challenges in meeting the growing needs of food security because of its low water availability. Maintaining and enhancing agricultural water productivity under such prevailing environmental constraints are hard to achieve. Potatoes water productively in Jordan Valley was modeled using Decision Support System for Agrotechnology Transfer (DSSAT) under six nitrogen applications (0, 60, 80, 100, 120 and 140 kg/ha) and twelve planting dates every two weeks from October 1 to March 15 scenarios. The potatoes yield increased from 0% to 100% nitrogen treatment and then no considerable increase occurred. The potatoes’ crop yield increased from October 1st to January 15 and then decreased after which until the last day of planting date. The seasonal cumulative crop evapotranspiration for potatoes about doubled from 0% to 60% nitrogen treatment and then kept increasing gradually until the last treatment. The growing season cumulative crop evapotranspiration for potatoes increased gradually from October 1 to March 1. The water productivity increased from 0% nitrogen treatment to 100% and then decreased. The potatoes’ water productivity increased from October 1 until November 15 and then decreased to the end. From these results, we recommend that 100% of nitrogen requirements should be applied. The best window for potatoes’ planting date is the last two weeks in November.

Spatio‐temporal variability of reference crop evapotranspiration at different timescales in Sichuan Province, south‐west China*

AbstractAiming to analyse the variation of seasonal reference crop evapotranspiration (ET0) and show the impact of meteorological factors on ET0 across Sichuan Province, this study mainly discussed the variation of ET0 during the periods of 1967–2016 in three subregions of Sichuan Province with the Mann–Kendall test (MK), Morlet wavelet analysis and path analysis. Meanwhile, future ET0 trend variation characteristics at different timescales were evaluated by Hurst exponents based on the rescaled range analysis (R/S) method. The results indicated that over the past 50 years, annual ET0 had a decreasing trend with a rate of −0.64 mm per10 years, confirming the existence of an ‘evaporation paradox’. Through spatial analysis, the distribution of average annual ET0 exhibited a declining trend from south to north over the study region. On the seasonal scale, the highest values of ET0 in summer were distributed in the Sichuan central basin while the highest values in other seasons were in the south‐western mountain area. The Hurst exponents showed that the trends of annual and seasonal ET0 in the future are consistent with past ones in the whole region (H &gt; 0.5). The annual ET0 showed the obvious periodic variation of 28 years in the study regions based on Morlet wavelet analysis. The decreases in ET0 were mostly attributed to the decline in sunshine hours. These findings can help water managers in better water planning and irrigation scheduling for local agricultural production.

Assessing evapotranspiration and crop coefficients of potato in a semi-arid climate using Eddy Covariance techniques

A correct estimation of crop coefficients (KC) is essential to assess water requirements of crops from weather variables and thereby optimize irrigation management. KC depends on crop type and varies with crop growth stage, and to a limited extent, with climate. KC values are often assumed to be transferable between locations and climates. KC values have not been determined yet for modern potato cultivars grown under South African, semi-arid climatic conditions. The objectives of this study were (i) to quantify evapotranspiration and water use efficiency (WUE) of potato crops in a semi-arid climate under irrigation, (ii) to estimate KC values for these crops at different growth stages, and (iii) to assess the usefulness of the Penman-Monteith equation to estimate evapotranspiration and irrigation requirements. An eddy covariance (ECV) system was used in potato fields planted with the variety Mondial in two production regions of South Africa: Limpopo (crop growing in winter) and North West (spring-summer crop). Additional sensors were added to the system to measure relative humidity, near surface soil temperature, solar radiation, rainfall and irrigation. Decagon 10 HS capacitance sensors installed at varying soil depths were used to measure the change in soil moisture content of the potato rooted zone. Accuracy of the ECV measurements was evaluated by following the energy balance closure method. Seasonal mean crop evapotranspiration (ETC) was 3.2 mm d−1 for the crop in Limpopo and 5.7 mm d−1 in North West. The reference evapotranspiration (ETO) correlated well with the daily patterns in ETC for most of the season. ETO thus serves as a useful indicator of ETC and can be used for irrigation scheduling of potato. Seasonal mean KC value was 0.99 for the crop in Limpopo and 0.78 in North West. While the KC value in Limpopo likely represented that for a crop free of water-stress, the crop growth in North West was likely somewhat limited by water availability. The winter crop had the highest WUE of 3.55 kg dry potato tuber m−3 of water evapotranspired, whilst WUE for the spring-summer crop was 3.03 kg m−3. This difference could be explained by differences in mean vapour pressure deficit between the growing seasons. To optimize WUE of potato growing in semi-arid, water scarce regions such as South Africa, it is advisable to grow crops in the coolest available growing season, outside the frost-prone period.