Seasonal ET Research Articles

Improving Representation of Deforestation Effects on Evapotranspiration in the E3SM Land Model

AbstractEvapotranspiration (ET) plays an important role in land‐atmosphere coupling of energy, water, and carbon cycles. Following deforestation, ET is typically observed to decrease substantially as a consequence of decreases in leaf area and roots and increases in runoff. Changes in ET (latent heat flux) revise the surface energy and water budgets, which further affects large‐scale atmospheric dynamics and feeds back positively or negatively to long‐term forest sustainability. In this study, we used observations from a recent synthesis of 29 pairs of adjacent intact and deforested FLUXNET sites to improve model parameterization of stomatal characteristics, photosynthesis, and soil water dynamics in version 1 of the Energy Exascale Earth System Model (E3SM) Land Model (ELMv1). We found that default ELMv1 predicts an increase in ET after deforestation, likely leading to incorrect estimates of the effects of deforestation on land‐atmosphere coupling. The calibrated model accurately represented the FLUXNET observed deforestation effects on ET. Importantly, the search for global optimal parameters converged at values consistent with recent observational syntheses, confirming the reliability of the calibrated physical parameters. Applying this improved model parameterization to the globe scale reduced the bias of annual ET simulation by up to ~600 mm/year. Analysis on the roles of parameters suggested that future model development to improve ET simulation should focus on stomatal resistance and soil water‐related parameterizations. Finally, our predicted differences in seasonal ET changes from deforestation are large enough to substantially affect land‐atmosphere coupling and should be considered in such studies.

Are we approaching a water ceiling to maize yields in the United States?

AbstractWhile annual precipitation in much of the US Corn Belt is likely to remain constant, atmospheric vapor pressure deficit (VPD), the driver of crop water loss (evapotranspiration; ET), is projected to increase from ~2.2 kPa today to ~2.7 kPa by mid‐century primarily due to the temperature increase. Without irrigation, it has been hypothesized that the increase in VPD will create a ceiling to future increases in maize yields. We calculated current and future growing season ET based on biomass, water use efficiency, and the amount of yield these levels of ET would support for maize production in the Midwest USA. We assumed that the production of more grain will necessitate a proportional increase in the production of biomass, with a corresponding increase in ET. Here we show that as VPD increases, maintaining current maize yields (2013–2016) will require a large expansion of irrigation, greater than threefold, in areas currently supported by rain. The average predicted yield for the region of 244 ± 4 bushels/acre (15,316 ± 251 kg/ha) projected for 2050, assuming yield increases observed for the past 60 yr continue, would not be possible with projected increases in VPD, creating a water ceiling to maize yields. Substantial increases in maize yields and the production of high yielding grasses for bioenergy will require developing cultivars with greater water use efficiency, a trait that has not been a priority for breeders in the past.

Combining biophysical parameters, spectral indices and multivariate hyperspectral models for estimating yield and water productivity of spring wheat across different agronomic practices.

Manipulating plant densities under different irrigation rates can have a significant impact on grain yield and water use efficiency by exerting positive or negative effects on ET. Whereas traditional spectral reflectance indices (SRIs) have been used to assess biophysical parameters and yield, the potential of multivariate models has little been investigated to estimate these parameters under multiple agronomic practices. Therefore, both simple indices and multivariate models (partial least square regression (PLSR) and support vector machines (SVR)) obtained from hyperspectral reflectance data were compared for their applicability for assessing the biophysical parameters in a field experiment involving different combinations of three irrigation rates (1.00, 0.75, and 0.50 ET) and five plant densities (D1: 150, D2: 250, D3: 350, D4: 450, and D5: 550 seeds m-2) in order to improve productivity and water use efficiency of wheat. Results show that the highest values for green leaf area, aboveground biomass, and grain yield were obtained from the combination of D3 or D4 with 1.00 ET, while the combination of 0.75 ET and D3 was the best treatment for achieving the highest values for water use efficiency. Wheat yield response factor (ky) was acceptable when the 0.75 ET was combined with D2, D3, or D4 or when the 0.50 ET was combined with D2 or D3, as the ky values of these combinations were less than or around one. The production function indicated that about 75% grain yield variation could be attributed to the variation in seasonal ET. Results also show that the performance of the SRIs fluctuated when regressions were analyzed for each irrigation rate or plant density specifically, or when the data of all irrigation rates or plant densities were combined. Most of the SRIs failed to assess biophysical parameters under specific irrigation rates and some specific plant densities, but performance improved substantially for combined data of irrigation rates and some specific plant densities. PLSR and SVR produced more accurate estimations of biophysical parameters than SRIs under specific irrigation rates and plant densities. In conclusion, hyperspectral data are useful for predicting and monitoring yield and water productivity of spring wheat across multiple agronomic practices.

Determination of Crop Co-efficient Values for Jute (Corchorus olitorius L.)

Site specific calibration of crop coefficient (Kc) values is essential for irrigation scheduling of any crop. In order to determine the values of Kc for jute, an experiment was conducted at the Irrigation and Water Management Division of Bangladesh Agricultural Research Institute (BARI), Gazipur. An improved jute variety BJRI Tosa-2 (O-9897) was used in this experiment. The study examined growth and yield of the jute in terms of four irrigation treatments distributed over 7-28 days intervals. The treatments were so designed that drainage was allowed between the consecutive irrigations. Irrigation at 14days interval produced the highest dry fiber yield (3.93 t/ha) and was considered to be suitable for estimating seasonal crop evapotranspiration and Kc values. The seasonal crop ET was 549.13 mm under this treatment. The Kc values of jute at initial, development, mid-season and late season stages were found to be 0.72, 1.39, 1.26 and 0.46, respectively. As there is no FAO-recommended Kc value for this crop, this locally calibrated values can be used for similar climatic conditions of Bangladesh and elsewhere. Therefore, based on Kc value, it can be recommended that jute can be irrigated by equal amount of water needed for crop evapotranspiration (ETc) for different growth stages (141.05, 142.57, 167.34, and 84.30 mm) to get maximum dry fiber yield.
 The Agriculturists 2018; 16(2) 115-122

Evapotranspiration variations in the Yangtze River Basin from multi-satellite remote sensing data

Abstract Evapotranspiration (ET) variations in the Yangtze River Basin (YRB) are influenced by environmental and climate changes related to planting of crops, forest vegetation, water use and other human activities. However, it is difficult to measure ET variations and analyse influencing factors in the YRB due to lack of in-situ measurements. In the present study, the ET variations were estimated and investigated in the whole, the upper, middle and lower reaches of the YRB using the Gravity Recovery and Climate Experiment (GRACE), optical remote sensing data and hydrological models based on a water balance method, which was validated by MODerate Resolution Imaging Spectroradiometer (MODIS) observations and models. Furthermore, GRACE-ET verified the drought events in 2006 and 2011. The long-term variation rate of GRACE-ET is 0.79 mm/yr. The spatial distribution of seasonal ET variations indicates that ET is highest in summer and lowest in autumn-winter. It also shows that the completion of the Three Gorges Project has certainly increased ET. Precipitation and temperature have the largest impact on the ET variations; radiation and soil moisture have moderate effects. ET variations in the middle and lower reaches are greatly affected by precipitation, and temperature plays a more important role in the upper YRB reaches.

Interaction Effects of Planting Method, Irrigation Regimes, and Nitrogen Application Rates on Yield, Water and Nitrogen Use Efficiencies of Winter Wheat (Triticum aestivum)

Arid and semi-arid regions in the world that produce wheat (Triticum aestivum) are faced with frequent droughts in recent years. Moreover, wheat production is highly dependent on irrigation and it is essential to increase irrigation water productivity in these regions. Therefore, the aim of this study was to investigate the effects of irrigation methods, planting methods, and nitrogen application rates on yield, water and nitrogen use efficiencies of winter wheat. The experiment arranged in split–split plot with randomized blocks with two surface irrigation methods [ordinary furrow irrigation (OFI) and variable alternate furrow irrigation (VAFI)] as the main plots, two planting methods [on-ridge planting (ORP) and in-furrow planting] as the sub plots, and three nitrogen application rates (N0 = 0, N1 = 150 and N2 = 300 kg N ha−1) as the sub–sub plot. Results indicated that VAFI reduced the winter wheat grain yield, dry matter, grain number per spike, and harvest index as 12, 9, 3, and 4%, respectively; however, these reductions were not significant in comparison with OFI method with a reduction of 33% in irrigation water; as a consequence, the straw nitrogen concentration, grain protein concentration, and also water use efficiencies (WUE), irrigation water productivity (IWP), economic irrigation water productivity (EIWP) and nitrogen use efficiency (NUE) were improved in VAFI as 14, 5, 6, 26, 25, and 8%, respectively. In spite of a slight reduction in grain yield, VAFI method increased EIWP. Economic nitrogen productivity decreased about 50% by increase in N rate, and 150 kg N ha−1 was the optimum rate to apply. Furthermore, VAFI decreased the seasonal ET, thereby improved WUE and IWP. In-furrow planting increased significantly the WUES while it did not enhance significantly WUE for grain. Generally, increasing the nitrogen rate increased the grain yield; whereas, there was no significant difference between the treatments of 150 and 300 kg N ha−1. Results suggest that application of 150 kg N ha−1 combined with in-furrow planting method and variable alternate furrow irrigation is an effective way to improve WUE, yield, yield components and NUE for winter wheat in the study area.

Possibilities of using dual K c approach in predicting crop evapotranspiration of second-crop silage maize

The purposes of this study were to develop a dual crop coefficient (K c ) using FAO-56 methodologies and to compare crop evapotranspiration (ETK c ) measured under field conditions for second-crop silage maize in the Southeastern Anatolia Region of Turkey with the ET c estimated using FAO-56 dual K c methodologies. For this study, field experiments were conducted in the 2011 and 2012 growing seasons, and the results were evaluated. To compute dual K c (K cb and K e ), all climatological data involving the seedling and harvesting dates, growth stages, water holding of soil at field capacity and at wilting point, soil evaporation layer, and crop characteristics were input into a spreadsheet program. The crop stages observed were 15, 25, 40, and 12 days for the initial, crop development, midseason, and late-season stages, respectively, in 2011, and 12, 23, 43, and 13 days, respectively, for the same stages in 2012. The reference evapotranspiration (ET o ) was computed daily using the Penman-Monteith equation. All main and intermediate calculations for the dual Kc and its components K cb and K e were based on the FAO-56 guidelines. The K cb values were computed as 0.15, 1.27, and 0.62 for the initial, midseason, and late-season stages, respectively. However, these figures were 0.15, 1.15, and 0.5 in the FAO-56 in the same order. The dual K c was 0.64, 1.27, and 0.67 in this study for the initial, midseason, and late-season stages, respectively. The maximum ET c rate occurred in midseason, which had an average maximum value of 10.8 mm day -1 . The ET c of silage maize for optimal dry matter during the growing season in the years of the study was 519 mm as the average of two growing seasons. The FAO methodology thus insignificantly overestimated the seasonal ET c (536 mm) for silage maize. Thus, the FAO-56 dual K c methodology can be used to estimate the crop ET c .

Application of an energy balance method for estimating evapotranspiration in cropping systems

Accurate quantification of evapotranspiration (ET, consumptive water use) from planting through harvest is critical for managing limited water resources for crop irrigation. Our objective was to develop and apply a land-crop surface residual energy balance (EB) method for quantifying ET and to estimate ET of corn (Zea mays L.) for the first time in the climate of the lower Mississippi Delta region. Actual ET (ETe) was estimated as the residual term of the energy balance equation from measurements of net solar irradiance (Rn) and computed sensible heat (H) and ground heat (Go) fluxes. The H flux was computed from measurements of the air and crop canopy temperature differential and modeling the aerodynamic resistance (ra) to heat and water transport in the turbulent atmospheric boundary layer above the canopy. The Go flux was estimated by measuring heat flux at 8 cm depth and accounting for heat storage in the soil layer above it. The developed EB procedure was tested using simultaneous measurements of EB data and lysimetric ET in a cotton (Gossypium hirsutum L.) field at Bushland, Texas, USA in 2008. The lysimeter measured ET compared well with the computed ETe under cotton (RMSE of daily ET = 1.2 mm, and seasonal ET within 1% error). Further, we quantified irrigated corn ET using EB in a silt loam soil at Stoneville, Mississippi, USA in 2016. The computed seasonal values of ETe were greater than shortgrass reference ET (ETo) by 27 mm and less than alfalfa reference crop ET (ETr) by 80 mm. The instrumentation used in the EB method can be moved, and the estimated ET was comparable with lysimeter measured ET. As such, this method provides a cost-effective, viable alternative for quantifying ET, which should be broadly tested in other locations and cropping systems.

Yield production functions of irrigated sugarbeet in an arid climate

Increased water demands and drought have resulted in the need to provide data to guide deficit water management decisions in irrigated sugarbeet (Beta vulgaris L.) production. The objective of this study was to quantify the yield response of sugarbeet to water input and actual crop evapotranspiration (ETa) on a soil type (silt loam) common to sugarbeet production in the Northwest U.S. These relationships are valuable to understanding sugarbeet response over a range of water availability and in developing tools to assess future production under water shortages. This paper consolidates data from three studies consisting of ten site-years from 2009 to 2016. The studies were at the USDA-Agricultural Research Service facility in Kimberly, ID on a Portneuf silt loam soil. Treatments consisted of varying levels of cumulative seasonal Kimberly-Penman ET model estimated crop evapotranspiration (ETc) rates ranging from rain-fed to 125% of ETc. Irrigation methods consisted of surface drip irrigation (3 site-years), linear/pivot overhead sprinkler (6 site-years), and solid-set sprinkler (1 site-year). Irrigation frequency was consistent for all studies with applications occurring 2–3 times per week depending on ETc demand. Estimated recoverable sucrose (ERS) yield and root yield were measured, and soil water contents were measured. Across all site-years, quantitative relationships between both actual crop ET (ETa) and water input, and sugarbeet yield and quality variables were developed. Significant (0.05 probability level) positive linear relationships were found between ETa and sugarbeet ERS and root yields (r2 = 0.78). Estimated recoverable sucrose and root yields increased at rates of 19.4 kg ha−1 mm−1 ETa and 0.13 Mg ha−1 mm−1 ETa, respectively. When ETa depths of 719 and 729 mm were reached by the crop, root and ERS yields were maximized, respectively. When water input (irrigation + precipitation) depths of 598 and 605 mm were applied root and ERS yields were maximized, respectively. The quantitative relationships between both ETa and water input, and sugarbeet yields can be used to quantify sugarbeet production under deficit irrigation conditions (data derived from pivot/linear, drip, and solid set irrigation types), which may arise due to water shortage scenarios, or when drought occurs in non-irrigated areas.

Assessing Irrigation Aquifer Depletion: Introduction

Assessing Irrigation Aquifer Depletion: Introduction

Modeling the hydrological impacts of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia

Understanding the hydrological response of a watershed to land use/land cover (LULC) changes is imperative for water resources management planning. The objective of this study was to analyze the hydrological impacts of LULC changes in the Andassa watershed for a period of 1985–2015 and to predict the LULC change impact on the hydrological status in year 2045. The hybrid land use classification technique for classifying Landsat images (1985, 2000 and 2015); Cellular-Automata Markov (CA-Markov) for prediction of the 2030 and 2045 LULC states; the Soil and Water Assessment Tool (SWAT) for hydrological modeling were employed in the analyses. In order to isolate the impacts of LULC changes, the LULC maps were used independently while keeping the other SWAT inputs constant. The contribution of each of the LULC classes was examined with the Partial Least Squares Regression (PLSR) model. The results showed that there was a continuous expansion of cultivated land and built-up area, and withdrawing of forest, shrubland and grassland during the 1985–2015 periods, which are expected to continue in the 2030 and 2045 periods. The LULC changes, which had occurred during the period of 1985 to 2015, had increased the annual flow (2.2%), wet seasonal flow (4.6%), surface runoff (9.3%) and water yield (2.4%). Conversely, the observed changes had reduced dry season flow (2.8%), lateral flow (5.7%), groundwater flow (7.8%) and ET (0.3%). The 2030 and 2045 LULC states are expected to further increase the annual and wet season flow, surface runoff and water yield, and reduce dry season flow, groundwater flow, lateral flow and ET. The change in hydrological components is a direct result of the significant transition from the vegetation to non-vegetation cover in the watershed. This suggests an urgent need to regulate the LULC in order to maintain the hydrological balance.

Assessing the climate change impact on hydrological response in the Gorganrood River Basin, Iran

Abstract A general circulation model (GCM) and hydrological model SWAT (Soil and Water Assessment Tool) under forcing from A1B, B1, and A2 emission scenarios by 2030 were used to assess the implications of climate change on water balance of the Gorganrood River Basin (GRB). The results of MPEH5C models and multi-scenarios indicated that monthly precipitation generally decreases while temperature increases in various parts of the basin with the magnitude of the changes in terms of different stations and scenarios. Accordingly, seasonal ET will decrease throughout the GRB over the 2020s in all seasons except in summer, where a slight increase is projected for A1B and A2 scenarios. At annual scale, average quick flow and average low flow under the B1, A1B, and A2 scenarios are projected to decrease by 7.3 to 12.0% from the historical levels. Over the ensembles of climate change scenarios, the simulations project average autumn total flow declines of ∼10% and an overall range of 6.9 to 13.2%. In summer, the components of flow at the studied basin are expected to increase under A2 and A1B scenarios but will slightly decrease under B1 scenario. The study result addresses a likelihood of inevitable future climate change.

Water use efficiency for grain yield in an old and two more recent maize hybrids

Increasing water use efficiency for grain production, WUEg (i.e. the quotient between grain yield and seasonal evapotranspiration, ET) is of relevance in rainfed crops. A greater WUEg is expected in more recent than in old maize (Zea mays L.) hybrids, based on different reports indicating higher grain yield, higher stress tolerance or similar seasonal ET in more recent than in old maize hybrids. However, there are no reports quantifying WUEg in maize hybrids released in different decades. In this study we quantify WUEg and its components (i.e. grain yield and seasonal ET) and we examine physiological traits during the critical period for kernel set (i.e. plant growth rate, PGRcp; ear growth rate, EGRcp; ET, ETcp and stomatal conductance), in an old and in two more recent maize hybrids grown under contrasting soil water availability. Three maize hybrids, DK2F10 (old hybrid released in 1980) and DK682RR and DK690MG (more recent hybrids, released in 2004), were grown in 5 experiments during 4 seasons; and irrigation and rainfed treatments were used to promote contrasting soil water availabilities. Soil water content was measured every 7–10days with a neutron probe. Maximum WUEg tended to be higher for more recent (25.1kgha−1mm−1) than for the older hybrid (23.1kgha−1mm−1); and advantages of WUEg were larger and significantly higher in the more recent than in the older hybrid, at lower water availability. The greater WUEg of more recent hybrids was associated with greater grain yield at all water supplies; which was the result of a greater KNP. At low water availability, the greater KNP in more recent hybrids was related to greater PGRcp, ETcp and stomatal conductance than in the old maize hybrid.

Implications of non-sustainable agricultural water policies for the water-food nexus in large-scale irrigation systems: A remote sensing approach

Abstract This study proposes a novel monitoring tool based on Satellite Remote Sensing (SRS) data to examine the status of water distribution and Water Use Efficiency (WUE) under changing water policies in large-scale and complex irrigation schemes. The aim is to improve our understanding of the water-food nexus in such schemes. With a special reference to the Gezira Irrigation Scheme (GeIS) in Sudan during the period 2000–2014, the tool devised herein is well suited for cases where validation data are absent. First, it introduces an index, referred to as the Crop Water Consumption Index (CWCI), to assess the efficiency of water policies. The index is defined as the ratio of actual evapotranspiration (ET a ) over agricultural areas to total ET a for the whole scheme where ET a is estimated using the Simplified Surface Energy Balance model (SSEB). Second, the tool uses integrated Normalized Difference Vegetation Index (iNDVI), as a proxy for crop productivity, and ET a to assess the WUE. Third, the tool uses SSEB ET a and NDVI in an attempt to detect wastage of water. Four key results emerged from this research as follows: 1) the WUE has not improved despite the changing agricultural and water policies, 2) the seasonal ET a can be used to detect the drier areas of GeIS, i.e. areas with poor irrigation water supply, 3) the decreasing trends of CWCI, slope of iNDVI-ET a linear regression and iNDVI are indicative of inefficient utilization of irrigation water in the scheme, and 4) it is possible to use SSEB ET a and NDVI to identify channels with spillover problems and detect wastage of rainwater that is not used as a source for irrigation. In conclusion, the innovative tool developed herein has provided important information on the efficiency of a large-scale irrigation scheme to help rationalize laborious water management processes and increase productivity.

A Direct Estimate of the Seasonal Cycle of Evapotranspiration over the Amazon Basin

Abstract Evapotranspiration (ET) is a critical term in the surface energy budget as well as the water cycle. There are few direct measurements of ET, and thus the magnitude and variability are poorly constrained at large spatial scales. Estimates of the annual cycle of ET over the Amazon are critical because they influence predictions of the seasonal cycle of carbon fluxes, as well as atmospheric dynamics and circulation. The authors estimate ET for the Amazon basin using a water budget approach by differencing rainfall, discharge, and time-varying storage from the Gravity Recovery and Climate Experiment. It is found that the climatological annual cycle of ET over the Amazon basin upstream of Óbidos shows suppression of ET during the wet season and higher ET during the dry season, consistent with flux-tower-based observations in seasonally dry forests. They also find a statistically significant decrease in ET over the time period 2002–15 of −1.46 mm yr−1. The direct estimate of the seasonal cycle of ET is largely consistent with previous indirect estimates, including energy-budget-based approaches, an upscaled station-based estimate, and land surface model estimates, but suggests that suppression of ET during the wet season is underestimated by existing products.

Environmental controls on seasonal ecosystem evapotranspiration/potential evapotranspiration ratio as determined by the global eddy flux measurements

Abstract. The evapotranspiration / potential evapotranspiration (AET / PET) ratio is traditionally termed as the crop coefficient (Kc) and has been generally used as ecosystem evaporative stress index. In the current hydrology literature, Kc has been widely used as a parameter to estimate crop water demand by water managers but has not been well examined for other types of ecosystems such as forests and other perennial vegetation. Understanding the seasonal dynamics of this variable for all ecosystems is important for projecting the ecohydrological responses to climate change and accurately quantifying water use at watershed to global scales. This study aimed at deriving monthly Kc for multiple vegetation cover types and understanding its environmental controls by analyzing the accumulated global eddy flux (FLUXNET) data. We examined monthly Kc data for seven vegetation covers, including open shrubland (OS), cropland (CRO), grassland (GRA), deciduous broad leaf forest (DBF), evergreen needle leaf forest (ENF), evergreen broad leaf forest (EBF), and mixed forest (MF), across 81 sites. We found that, except for evergreen forests (EBF and ENF), Kc values had large seasonal variation across all land covers. The spatial variability of Kc was well explained by latitude, suggesting site factors are a major control on Kc. Seasonally, Kc increased significantly with precipitation in the summer months, except in EBF. Moreover, leaf area index (LAI) significantly influenced monthly Kc in all land covers, except in EBF. During the peak growing season, forests had the highest Kc values, while croplands (CRO) had the lowest. We developed a series of multivariate linear monthly regression models for Kc by land cover type and season using LAI, site latitude, and monthly precipitation as independent variables. The Kc models are useful for understanding water stress in different ecosystems under climate change and variability as well as for estimating seasonal ET for large areas with mixed land covers.

Simulation of the Responses of Dry Beans (Phaseolus vulgaris L.) to Irrigation

Abstract. AquaCrop is a crop simulation model developed by the FAO aimed at assessing the yield response to water supply. Once the model is calibrated and validated, it is a useful tool to simulate crop yields under different management options or climatic and soil conditions. Until now, AquaCrop has not been parameterized for dry beans ( L.), and thus our objective was to calibrate and validate the model for this crop using experiments performed 40 years ago at Davis, California. A set of parameters derived from the calibration with one irrigation experiment was used to validate the model using five experiments carried out in 1977 and 1978 that had treatments vastly differing in irrigation depth and frequency. Yield predictions over a wide range of values (<1 to 3.5 t ha-1) were very good, with RMSE of 0.16 t ha-1 and Willmott’s d of 0.978. Seasonal ET was also accurately predicted by the model (RMSE = 40 mm, d = 0.930), as also evidenced by comparing the lysimeter measured ET of 489 mm against the lysimeter simulated ET of 501 mm. Canopy cover and the time course of biomass were adequately simulated as well. Even though total soil water extraction was well simulated, the simulated soil water distribution with depth differed from measured values in the dryland treatment. We conclude that AquaCrop can now be used for the simulation of dry beans in different environments, and we emphasize the value of carefully conducted field experiments for the validation of crop simulation models. Keywords: AquaCrop, Calibration and validation, Dry beans (Phaseolus vulgaris L.), Irrigation, Simulation model, Water stress.

Responses of yield and WUE of winter wheat to water stress during the past three decades—A case study in the North China Plain

Improving grain yield and water use efficiency (WUE) under limited irrigation is very important for food security in water shortage regions. This paper summarized a long-term field experiment (from 1987 to 2015, 28 growing seasons of winter wheat) on the responses of winter wheat to different levels of water stress under the changing background of cultivars, soil fertility and weather conditions at a site in the North China Plain (NCP). The results showed that during the past 28 seasons soil organic matter and N contents were significantly increased at the experimental site and the atmospheric evaporation demand (ET0) was increased and seasonal rainfall was reduced. Although yield was continuously increased from 1987 to 2015 under irrigated condition, the yield of winter wheat under rain-fed condition decreased recently as compared with that during 2000s due to the higher ET0 and less seasonal rainfall. WUE was increased continuously from past to present, especially under water stress condition, indicating that the winter wheat used water more efficiently under the current growing conditions. This could be attributed to the increase in harvest index, improved N status in soil and the reduced soil evaporation. Overall, the sensitivity of grain yield to the fluctuation in seasonal ET was increased from 1980s to present. Yield reduction rate under water stress was greater under current growing conditions than that back in 1980s and 1990s. However, even with the changes in the responses to water stress, irrigation scheduling of one irrigation application from recovery to jointing for winter wheat could achieve relative stable yield and higher WUE through the 28 seasons and should be taken as optimized irrigation scheduling under limited water supply condition.

THE EFFECT OF IRRIGATION FREQUENCY AND RATE UNDER TRICKLE IRRIGATION MANAGEMENT ON YIELD GREEN BEAN GROWN IN CLAY LOAM SOIL

This study was conducted over 2 years (2013 and 2014) to establish the optimal combinations between irrigation frequency and rate for trickle-irrigated green bean using water production functions and water use– yield relationships. A field experiment was conducted using a randomized complete block design with three irrigation frequencies (F1, F2 and F3, irrigation events once every 1, 2and 3 days, respectively) and three trickle irrigation rates (I1: 1.00, I2: 0.80, and I3: 0.60 of the estimated evapotranspiration, ET). Our results show that yield variables and water use efficiencies (WUEs) increased with increasing irrigation frequency and rate, with non-significant differences between F1 and F2 in yield variables and between I1 and I2 in WUEs. Moreover, the combination between various irrigation frequencies and rates had an important effect on yield variables and WUEs, with the highest values being found with F1I2 and F2 I1 and the lowest for F2I3 and F3I3. The F1I3 treatment had grain yield and yield components values similar to those obtained for the F2I3 treatments and WUEs values similar to those obtained for the F2I3 and F3I1 treatments. Production functions of yield versus seasonal crop ET were linear for all combinations of irrigation frequency and rate and for all irrigation frequency treatments with the exception of the F1 treatment, which instead showed a second order relationship. In conclusion, we identified the optimal coupling combinations between irrigation frequency and water application rate to achieve the maximum yield and WUEs.

Review of Turfgrass Evapotranspiration and Crop Coefficients

Abstract. This review summarizes available data related to turfgrass evapotranspiration (ET c ) and crop coefficients (K c ) for both warm-season and cool-season grasses. Daily, monthly, or seasonal ET c rates and K c values determined at different locations in the U.S. are shown in this review, as well as the methods used to determine or estimate these values. Warm-season turfgrasses are characterized by their lower ET c rates compared to cool-season turfgrasses. Results showed that ET c is highly variable, not only between species but within same species. For example, ‘Tifway‘ bermudagrass, a warm-season turfgrass, showed ET c values of 1.78 mm d -1 in central Florida and 4.83 mm d -1 in Colorado, whereas zoysiagrass showed an ET c value of 9.40 mm d -1 in Texas. On the other hand, creeping bentgrass showed an ET c value of 3.3 mm d -1 for ‘Pennlinks‘ variety, while ‘Seaside‘ showed an ET c value of 10.7 mm d -1 , both in Nebraska. This variability was affected by genotype and plant morphological characteristics but was also due to weather conditions. Variability was also observed in turfgrass K c . Minimum and maximum monthly K c values for cool-season grasses were estimated as 0.05 and 1.05, respectively; for warm-season grasses, monthly K c values ranged from 0.28 to 0.99. The lowest reported K c values within a turfgrass species could serve as selection criteria to breed new varieties resistant to drought or contributing to water savings. Evapotranspiration rates and crop coefficients should be used with awareness of the local conditions under which the values were developed.