Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT model

In southwestern Ontario, rain-fed crop production frequently fails to achieve its yield potential because of growing-season droughts and/or uneven rainfall distribution. The objective of this study was to determine if the Decision Support System for Agrotechnology Transfer (DSSAT) v4.5 model could adequately simulate corn and soybean yields, near-surface soil water contents, and cumulative nitrate-N losses associated with regular free tile drainage (TD) and controlled tile drainage with optional subsurface irrigation (CDS). The simulations were compared to observations collected between 2000 and 2004 from both TD and CDS field experiments on a Perth clay loam soil at the Essex Region Conservation Authority demonstration farm, Holiday Beach, Ontario, Canada. There was good model-data agreement for crop yields, near-surface (0-30 cm) soil water content and cumulative annual tile nitrate-N loss in both the calibration and validation years. For both TD and CDS, the CENTURY soil C/N model in DSSAT simulated water content and cumulative tile nitrate-N loss with normalized root mean square error (n-RMSE) values ranging from 9.9 to 14.8% and 17.8 to 25.2%, respectively. The CERES-Maize and CROPGRO-Soybean crop system models in the DSSAT simulated corn and soybean yields with n-RMSE values ranging from 4.3 to 14.0%. It was concluded that the DSSAT v4.5 model can be a useful tool for simulating near-surface soil water content, cumulative tile nitrate-N losses, and corn and soybean yields associated with CDS and TD water management systems.     

Water use of spring wheat to raise water productivity

In semi-arid environments with a shortage of water resources and a risk of overexplotation of water supplies, spring wheat (Triticum aestivum L.) is a crop that can reduce water use and increase water productivity, because it takes advantage of spring rainfall and is harvested before the evaporative demands of summer. We carried out an experiment in 2003 at “Las Tiesas” farm, located between Barrax and Albacete (Central Spain), to improve accuracy in the estimation of wheat evapotranspiration (ETc) by using a weighing lysimeter. The measured seasonal ETc averages (5.63 mm day⁻¹) measured in the lysimeter was 417 mm compared to the calculated ETc values (5.31 mm day⁻¹) calculated with the standard FAO methodology of 393 mm. The evapotranspiration crop coefficient (Kc) derived from lysimetric measurements was Kc-mid: 1.20 and Kc-end: 0.15. The daily lysimeter Kc values were fit to the evolution linearly related to the green cover fraction (fc), which follows the crop development pattern. Seasonal soil evaporation was estimated as 135 mm and the basal crop coefficient approach was calculated in this study, Kcb which separates crop transpiration from soil evaporation (evaporation coefficient, Ke) was calculated and related to the green cover fraction (fc) and the Normalized Difference Vegetation Index (NDVI) obtained by field radiometry in case of wheat. The results obtained by this research will permit the reduction of water use and improvement of water productivity for wheat, which is of vital importance in areas of limited water resources.     

Simulated effect of drainage water management operational strategy on hydrology and crop yield for Drummer soil in the Midwestern United States

The hypothetical effects of drainage water management operational strategy on hydrology and crop yield at the Purdue University Water Quality Field Station (WQFS) were simulated using DRAINMOD, a field-scale hydrologic model. The WQFS has forty-eight cropping system treatment plots with 10 m drain spacing. Drain flow observations from a subset of the treatment plots with continuous corn (Zea mays L.) were used to calibrate the model, which was then used to develop an operational strategy for drainage water management. The chosen dates of raising and lowering the outlet during the crop period were 10 and 85 days after planting, respectively, with a control height of 50 cm above the drain (40 cm from the surface). The potential effects of this operational strategy on hydrology and corn yield were simulated over a period of 15 years from 1991 to 2005. On average, the predicted annual drain flows were reduced by 60% (statistically significant at 95% level). This is the most significant benefit of drainage water management since it may reduce the nitrate load to the receiving streams. About 68% of the reduced drain flow contributed to an increase in seepage. Drainage water management increased the average surface runoff by about 85% and slightly decreased the relative yield of corn crop by 0.5% (both are not statistically significant at 95% level). On average, the relative yield due to wet stress (RYw) decreased by 1.3% while relative yield due to dry stress (RYd) increased by 1%. Overall, the relative crop yield increased in 5 years (within a range of 0.8-6.9%), decreased in 8 years (within a range of 0.2-5.5%), and was not affected in the remaining 2 years. With simulated drainage water management, the water table rose above the conventional drainage level during both the winter and the crop periods in all years (except 2002 crop season). The annual maximum winter period rise ranged between 47 cm (1995) and 87 cm (1992), and the annual maximum crop period rise ranged between no effect (2002) and 47 cm (1993).     

Estimating yield of sorghum using root zone water balance model and spectral characteristics of crop in a dryland Alfisol

This study investigated the relationship between sorghum grain yield for a range of soil depths, with the seasonal crop water stress index based on relative evapotranspiration deficits and spectral vegetation indices. A root zone water balance model was used to evaluate seasonal soil water fluctuations and actual evapotranspiration within a toposequence; soil depth varied between 30 and 75 cm and available water capacity ranged from 6.9 to 12.6% (v/v, %). An empirical model was used to determine root growth. Runoff was estimated from rainfall data using the curve number techniques of the Soil Conservation Services, combined with a soil water-accounting procedure. The high r² values between modeled and observed values of soil water in the root zone (r² > 0.70, significant at P < 0.001) and runoff (r² = 0.95, significant at P < 0.001) indicated good agreement between the model output and observed values. Canopy reflectance was measured during the entire crop growth period and the following spectral indices were calculated: simple ratio, normalized difference vegetation index (NDVI), green NDVI, perpendicular vegetation index, soil adjusted vegetation index (SAVI) and modified SAVI (MSAVI). All the vegetation indices, except for the perpendicular vegetation index, measured from booting to anthesis stage, were positively correlated with leaf area index (LAI) and yield. The correlation coefficient for spectral indices with dry biomass was relatively less than for LAI and yield. Modified SAVI recorded from booting to milk-grain stage gave the highest average correlation coefficient with grain yield. Additive and multiplicative forms of water-production functions, as well as water stress index calculated from water budget model, were used to predict crop yield. A multiple regression was carried out with yield, for the years 2001–2003, as the dependent variable and MSAVI, from the booting to the milk-grain stage of crop and relative yield values, calculated using both additive and multiplicative water production functions as well as water stress index, as the independent variables. The multiplicative model and MSAVI, recorded during the heading stage of crop growth, gave the highest coefficient of determination (r² = 0.682, significant at P < 0.001). The multiple regression equation was tested for yield data recorded during 2004; the deviation between observed and estimated yields varied from −6.2 to 9.4%. The water budget model, along with spectral vegetation indices, gave satisfactory estimates of sorghum grain yields and appears to be a useful tool to estimate yield as a function of soil depth and available water.     

Intra-annual variability in the contribution of tile drains to basin discharge and phosphorus export in a first-order agricultural catchment

This study examines spatiotemporal variability (event-based, seasonal) in the contribution of drainage tiles within a basin to basin hydrologic discharge and soluble reactive phosphorus (SRP) and total phosphorus (TP) export over a period of 1 year. Tile discharge was highly variable at both moderate (wet versus dry periods) and smaller (within-event) temporal scales, accounting for 0-90% of basin discharge at any given time. An estimated 42% of basin annual discharge originated from drainage tiles, the majority of which occurred during the winter and spring months. Concentrations of SRP and TP in drainage tile effluent were also highly variable in space and time (1-2850 μg SRP L⁻¹, 5-8275 μg TP L⁻¹). Higher concentrations of SRP and TP were linked to fields receiving manure compared to fields receiving inorganic fertilizers. SRP export from tiles accounted for 118% of basin SRP export on average, although their contribution to basin SRP export ranged from 4 to 344% on 32 discrete dates during which all tiles in the basin were sampled for hydrochemistry. On the same 32 dates, tiles accounted for an average of 43% of basin TP export, although this ranged from 0 to 200%. Management options such as tile plugs and optimizing the timing and application rates of fertilizer should be explored to minimize nutrient export from tiles.     

Predicting effects of drainage water management in Iowa's subsurface drained landscapes

Long-term hydrologic simulations are presented predicting the effects of drainage water management on subsurface drainage, surface runoff and crop production in Iowa's subsurface drained landscapes. The deterministic hydrologic model, DRAINMOD was used to simulate Webster (fine-loamy, mixed, superactive, mesic) soil in a Continuous Corn rotation (WEBS_CC) with different drain depths from 0.75 to 1.20 m and drain spacing from 10 to 50 m in a combination of free and controlled drainage over a weather record of 60 (1945-2004) years. Shallow drainage is defined as drains installed at a drain depth of 0.75 m, and controlled drainage with a drain depth of 1.20 m restricts flow at the drain outlet to maintain a water table at 0.60 m below surface level during the winter (November-March) and summer (June-August) months. These drainage design and management modifications were evaluated against conventional drainage system installed at a drain depth of 1.20 m with free drainage at the drain outlet. The simulation results indicate the potential of a tradeoff between subsurface drainage and surface runoff as a pathway to remove excess water from the system. While a reduction of subsurface drainage may occur through the use of shallow and controlled drainage, these practices may increase surface runoff in Iowa's subsurface drained landscapes. The simulations also indicate that shallow and controlled drainage might increase the excess water stress on crop production, and thereby result in slightly lower relative yields. Field experiments are needed to examine the pathways of water movement, total water balance, and crop production under shallow and controlled drainage in Iowa's subsurface drained landscapes.     

Subsurface drainage to combat waterlogging and salinity in irrigated lands in India: Lessons learned in farmers’ fields

The introduction of irrigated agriculture in the arid and semi-arid regions of India has resulted in the development of the twin problem of waterlogging and soil salinization. It is estimated that nearly 8.4 million ha is affected by soil salinity and alkalinity, of which about 5.5 million ha is also waterlogged. Subsurface drainage is an effective tool to combat this twin problem of waterlogging and salinity and thus to protect capital investment in irrigated agriculture and increase its sustainability. In India, however, subsurface drainage has not been implemented on a large scale, in spite of numerous research activities that proved its potential. To develop strategies to implement subsurface drainage, applied research studies were set-up in five different agro-climatic sub-regions of India. Subsurface drainage systems, consisting of open and pipe drains with drain spacing varying between 45 and 150 m and drain depth between 0.90 and 1.20 m, were installed in farmers’ fields. The agro-climatic and soil conditions determine the most appropriate combination of drain depth and spacing, but the drain depths are considerably shallower than the 1.75 m traditionally recommended for the prevailing conditions in India. Crop yields in the drained fields increased significantly, e.g. rice with 69%, cotton with 64%, sugarcane with 54% and wheat with 136%. These increases were obtained because water table and soil salinity levels were, respectively, 25% and 50% lower than in the non-drained fields. An economic analysis shows that the subsurface drainage systems are highly cost-effective: cost-benefit ratios range from 1.2 to 3.2, internal rates of return from 20 to 58%, and the pay-back periods from 3 to 9 years. Despite these positive results, major challenges remain to introduce subsurface drainage at a larger scale. First of all, farmers, although they clearly see the benefits of drainage, are too poor to pay the full cost of drainage. Next, water users’ organisations, not only for drainage but also for irrigation, are not well established. Subsurface drainage in irrigated areas is a collective activity, thus appropriate institutional arrangements for farmers’ participation and organisation are needed. Thus, to assure that drainage gets the attention it deserves, policies have to be reformulated.     

The variable response of dryland corn yield to soil water content at planting

Farmers in the central Great Plains want to diversify crop rotations from the traditional monoculture system of winter wheat-fallow. Corn (Zea mays L.) could work well as a rotation crop, but inputs are expensive and farmers would like to know the chances of producing a certain yield before investing in seed, fertilizer, herbicides, etc. Information on the yield response of corn to available soil water at planting could help guide the crop choice decision regarding corn. This study was conducted to determine if a predictive relationship exists between dryland corn yield and available soil water at planting time and, if such a relationship exists, to use it to assess the risk in obtaining profitable yields. Yield and soil water data from 10 years of a dryland crop rotation study at Akron, CO were analyzed by linear regression to determine predictive relationships. The yield-soil water content production function was highly variable, with values ranging from 0.0 to 67.3 kg ha⁻¹ per mm of available soil water in the 0 to 1.8 m soil profile at planting. The differences in yield response to soil water were related to the amount and timing of precipitation that fell during the corn growing season. Because dryland corn yield is highly dependent on precipitation during reproductive and grain-filling stages, soil water content at corn planting cannot be used alone to reliably determine whether corn should be planted in a flexible rotational system. The predictive relationships developed in this study indicate that under typical amounts of available soil water at corn planting, profitable corn production under dryland conditions is a risky and speculative activity in the central Great Plains of the United States.     

Using radiation thermography and thermometry to evaluate crop water stress in soybean and cotton

The use of digital infrared thermography and thermometry to investigate early crop water stress offers a producer improved management tools to avoid yield declines or to deal with variability in crop water status. This study used canopy temperature data to investigate whether an empirical crop water stress index could be used to monitor spatial and temporal crop water stress. Different irrigation treatment amounts (100%, 67%, 33%, and 0% of full replenishment of soil water to field capacity to a depth of 1.5 m) were applied by a center pivot system to soybean (Glycine max L.) in 2004 and 2005, and to cotton (Gossypium hirsutum L.) in 2007 and 2008. Canopy temperature data from infrared thermography were used to benchmark the relationship between an empirical crop water stress index (CWSI_e) and leaf water potential (Ψ_L) across a block of eight treatment plots (of two replications). There was a significant negative linear correlation between midday Ψ_L measurements and the CWSI_e after soil water differences due to irrigation treatments were well established and during the absence of heavy rainfall. Average seasonal CWSI_e values calculated for each plot from temperature measurements made by infrared thermometer thermocouples mounted on a center pivot lateral were inversely related to crop water use with r² values >0.89 and 0.55 for soybean and cotton, respectively. There was also a significant inverse relationship between the CWSI_e and soybean yields in 2004 (r² = 0.88) and 2005 (r² = 0.83), and cotton in 2007 (r² = 0.78). The correlations were not significant in 2008 for cotton. Contour plots of the CWSI_e may be used as maps to indicate the spatial variability of within-field crop water stress. These maps may be useful for irrigation scheduling or identifying areas within a field where water stress may impact crop water use and yield.     

Response of soybean genotypes to different irrigation regimes in a humid region of the southeastern USA

Studies on irrigation scheduling for soybean have demonstrated that avoiding irrigation during the vegetative growth stages could result in yields as high as those obtained if the crop was fully irrigated during the entire growing season. This could ultimately also lead to an improvement of the irrigation water use efficiency. The objective of this study was to determine the effect of different irrigation regimes (IRs) on growth and yield of four soybean genotypes and to determine their irrigation water use efficiency. A field experiment consisting of three IR using a lateral move sprinkler system and four soybean genotypes was conducted at the Bledsoe Research Farm of The University of Georgia, USA. The irrigation treatments consisted of full season irrigated (FSI), start irrigation at flowering (SIF), and rainfed (RFD); the soybean genotypes represented maturity groups (MGs) V, VI, VII, and VIII. A completely randomized block design in a split-plot array with four replicates was used with IR as the main treatment and the soybean MGs as the sub-treatment. Weather variables and soil moisture were recorded with an automatic weather station located nearby, while rainfall and irrigation amounts were recorded with rain gauges located in the experimental field. Samplings for growth analysis of the plant and its components as well as leaf area index (LAI) and canopy height were obtained every 12 days. The irrigation water use efficiency (I_WUE) or ratio of the difference between irrigated and rainfed yield to the amount of irrigation water applied was estimated. The results showed significant differences (P < 0.05) between IR for dry matter of the plant and its components, canopy height, and maximum leaf area index as well as significant differences (P < 0.05) between MGs due to IR. Differences for the interaction between IR and MG were significant (P < 0.05) only for dry matter of pods and seed yield. In general, seed yield increased at a rate of 7.20 kg for each mm of total water received (rainfall + irrigation) by the crop. Within IR, significant differences (P < 0.05) on I_WUE were found between maturity groups with values as low as 0.55 kg m⁻³ for MG V and as high as 1.14 kg m⁻³ for MG VI for the FSI treatment and values as low as 0.48 kg m⁻³ for maturity group V and as high as 1.02 kg m⁻³ for maturity group VI for the SIF treatment. We also found that there were genotypic differences with respect to their efficiency to use water, stressing the importance of cultivar selection as a key strategy for achieving optimum yields with reduced use of water in supplemental irrigation.     

Cover crop effects on nitrogen load in tile drainage from Walnut Creek Iowa using root zone water quality (RZWQ) model

Studies quantifying winter annual cover crop effects on water quality are mostly limited to short-term studies at the plot scale. Long-term studies scaling-up water quality effects of cover crops to the watershed scale provide more integrated spatial responses from the landscape. The objective of this research was to quantify N loads from artificial subsurface drainage (tile drains) in a subbasin of the Walnut Creek, Iowa (Story county) watershed using the hybrid RZWQ-DSSAT model for a maize (Zea mays L.)-soybean [Glycine max (L.) Merr.] and maize-maize-soybean rotations in all phases with and without a winter wheat (Triticum aestivum L.) cover crop during a 25-year period from 1981 to 2005. Simulated cover crop dry matter (DM) and N uptake averaged 1854 and 36 kg ha⁻¹ in the spring in the maize-soybean phase of the 2-year rotation and 1895 and 36 kg ha⁻¹ in the soybean-maize phase during 1981-2005. In the 3-year rotation, cover crop DM and N uptake averaged 2047 and 44 kg ha⁻¹ in the maize-maize-soybean phase, 2039 and 43 kg ha⁻¹ in the soybean-maize-maize phase, and 1963 and 43 kg ha⁻¹ in the maize-soybean-maize phase during the same period. Annual N loads to tile drains averaged 29 kg ha⁻¹ in the maize-soybean phase and 25 kg ha⁻¹ in the soybean-maize phase compared to 21 and 20 kg ha⁻¹ in the same phases with a cover crop. In the 3-year rotation, annual N loads averaged 46, 43, and 45 kg ha⁻¹ in each phase of the rotation without a cover crop and 37, 35, and 35 kg ha⁻¹ with a cover crop. These results indicate using a winter annual cover crop can reduce annual N loads to tile drains 20-28% in the 2-year rotation and 19-22% in the 3-year rotation at the watershed subbasin scale over a 25-year period.     

Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops

Irrigation performance and water productivity can be benchmarked if estimates of spatially distributed yield and crop water use are available. A commonly used method to estimate crop evapotranspiration in irrigated areas is to multiply reference evapotranspiration values by appropriate crop coefficients. This study evaluated convenient ways to derive such coefficients using multispectral vegetation indices obtained by remote sensing. Detailed ground radiometric measurements were taken in small plots perpendicular to the crop rows to obtain canopy reflectance values. Ancillary measurements of green ground cover, plant height, leaf area index and biomass were taken in the cropped strip covered by the radiometer field-of-view. The results were up-scaled using 10 Landsat-5 and 1 Landsat-7 images. Crop measurements and ground radiometry were made at the time of Landsat overpass on two commercial fields, one grown with sugarbeet and the other with cotton. Crop height and ground cover were determined weekly in these two fields, three additional sugarbeet fields and one additional cotton field. The ground and satellite observations of canopy reflectance yielded similar results. Two vegetation indices, the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI) were evaluated. Both indices described the crop growth well, but SAVI was used in further evaluations because it could be conveniently related to both ground cover and the basal crop coefficient using a simple model. Based on these findings, crop water use variability was analyzed in a large sample of sugarbeet and cotton fields, within a homogeneous irrigation scheme in Southern Spain. The yield versus evapotranspiration data points were highly scattered for both cotton and sugarbeet. The yield values obtained from the sugarbeet fields and cotton fields were substantially lower than values predicted by a linear yield function, and close to a curvilinear yield function, respectively. Evapotranspired water productivity varied in the cotton fields from 0.3 to 0.78 kg m⁻³, and in the sugarbeet fields from 7.15 to 14.8 kg m⁻³.     

Evaluation of the DRAINMOD-N II model for predicting nitrogen losses in a loamy sand under cultivation in south-east Sweden

The DRAINMOD-N II model (version 6.0) was evaluated for a cold region in south-east Sweden. The model was field-tested using four periods between 2002 and 2004 of climate, soil, hydrology and water quality data from three experimental plots, planted to a winter wheat-sugarbeet-barley-barley crop rotation and managed using conventional and controlled drainage. DRAINMOD-N II was calibrated using data from a conventional drainage plot, while data sets from two controlled drainage plots were used for model validation. The model was statistically evaluated by comparing simulated and measured drain flows and nitrate-nitrogen (NO₃-N) losses in subsurface drains. Soil mineral nitrogen (N) content was used to evaluate simulated N dynamics. Observed and predicted NO₃-N losses in subsurface drains were in satisfactory agreement. The mean absolute error (MAE) in predicting NO₃-N drainage losses was 0.16 kg N ha⁻¹ for the calibration plot and 0.21 and 0.30 kg N ha⁻¹ for the two validation plots. For the simulation period, the modelling efficiency (E) was 0.89 for the calibration plot and 0.49 and 0.55 for the validation plots. The overall index of agreement (d) was 0.98 for the calibration plot and 0.79 and 0.80 for the validation plots. These results show that DRAINMOD-N II is applicable for predicting NO₃-N losses from drained soil under cold conditions in south-east Sweden.     

Efficiency of controlled drainage and subirrigation in reducing nitrogen losses from agricultural fields

In northeast Italy, a regimen of controlled drainage in winter and subirrigation in summer was tested as a strategy for continuous water table management with the benefits of optimizing water use and reducing unnecessary drainage and nitrogen losses from agricultural fields.To study the feasibility and performance of water table management, an experimental facility was set up in 1996 to reproduce a hypothetical 6-ha agricultural basin with different land drainage systems existing in the region. Four treatments were compared: open ditches with free drainage and no irrigation (O), open ditches with controlled drainage and subirrigation (O-CI), subsurface corrugated drains with free drainage and no irrigation (S), subsurface corrugated drains with controlled drainage and subirrigation (S-CI). As typically in the region free drainage ditches were spaced 30 m apart, and subsurface corrugated drains were spaced 8 m apart.Data were collected from 1997 to 2003 on water table depth, drained volume, nitrate-nitrogen concentration in the drainage water, and nitrate-nitrogen concentration in the groundwater at various depths up to 3 m.Subsurface corrugated drains with free drainage (S) gave the highest measured drainage volume of the four regimes, discharging, on average, more than 50% of annual rainfall, the second-highest concentration of nitrate-nitrogen in the drainage water, and the highest nitrate-nitrogen losses at 236 k ha⁻¹.Open ditches with free drainage (O) showed 18% drainage return of rainfall, relatively low concentration of nitrate-nitrogen in the drainage water, the highest nitrate-nitrogen concentration in the shallow groundwater, and 51 kg ha⁻¹ nitrate-nitrogen losses.Both treatments with controlled drainage and subirrigation (O-CI and S-CI) showed annual rainfall drainage of approximately 10%. O-CI showed the lowest nitrate-nitrogen concentration in the drainage water, and the lowest nitrogen losses (15 kg ha⁻¹). S-CI showed the highest nitrate-nitrogen concentration in the drainage water, and 70 kg ha⁻¹ nitrate-nitrogen losses. Reduced drained volumes resulted from the combined effects of reduced peak flow and reduced number of days with drainage.A linear relationship between daily cumulative nitrate-nitrogen losses and daily cumulative drainage volumes was found, with slopes of 0.16, 0.12, 0.07, and 0.04 kg ha⁻¹ of nitrate-nitrogen lost per mm of drained water in S-CI, S, O, and O-CI respectively.These data suggest that controlled drainage and subirrigation can be applied at farm scale in northeast Italy, with advantages for water conservation.     

Crop water deficit estimation and irrigation scheduling in western Jilin province,Northeast China

Jilin province is one of the main dryland grain production areas in China. Recently, limited supplemental irrigation, using groundwater in the semi-arid western area of the province, has developed rapidly to improve the low grain productivity caused by rainfall variability. Research was conducted to estimate the actual crop water requirements and identify the timing and magnitude of water deficits of the main crops such as corn (Zea mays L.), soybean (Glycine max L.) and sorghum (Sorghum bicolor L.). Using the guidelines for computing crop water requirements in FAO Irrigation and Drainage paper 56 and historical rainfall distributions, the crop water requirements, ETc and the crop water deficits of corn, soybean and sorghum were calculated. Based on the water deficit analysis, a recommended average supplemental irrigation schedule was developed. Crop production was compared to full irrigation and to a rainfed control in a field experiment.On average, compared to the rainfed control, the full irrigation and the average supplemental irrigation treatments of corn, increased yields 49.0 and 43.9%, respectively; soybean yields of those treatments increased by 41.0 and 34.7%, and sorghum yields of those treatments increased by 55.5 and 46.3%. A supplemental irrigation schedule can be used in the semi-arid western Jilin province to improve crop yields.     

Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass

Water regulations have decreased irrigation water supplies in Nebraska and some other areas of the USA Great Plains. When available water is not enough to meet crop water requirements during the entire growing cycle, it becomes critical to know the proper irrigation timing that would maximize yields and profits. This study evaluated the effect of timing of a deficit-irrigation allocation (150 mm) on crop evapotranspiration (ETc), yield, water use efficiency (WUE = yield/ETc), irrigation water use efficiency (IWUE = yield/irrigation), and dry mass (DM) of corn (Zea mays L.) irrigated with subsurface drip irrigation in the semiarid climate of North Platte, NE. During 2005 and 2006, a total of sixteen irrigation treatments (eight each year) were evaluated, which received different percentages of the water allocation during July, August, and September. During both years, all treatments resulted in no crop stress during the vegetative period and stress during the reproductive stages, which affected ETc, DM, yield, WUE and IWUE. Among treatments, ETc varied by 7.2 and 18.8%; yield by 17 and 33%; WUE by 12 and 22%, and IWUE by 18 and 33% in 2005 and 2006, respectively. Yield and WUE both increased linearly with ETc and with ETc/ETp (ETp = seasonal ETc with no water stress), and WUE increased linearly with yield. The yield response factor (ky) averaged 1.50 over the two seasons. Irrigation timing affected the DM of the plant, grain, and cob, but not that of the stover. It also affected the percent of DM partitioned to the grain (harvest index), which increased linearly with ETc and averaged 56.2% over the two seasons, but did not affect the percent allocated to the cob or stover. Irrigation applied in July had the highest positive coefficient of determination (R²) with yield. This high positive correlation decreased considerably for irrigation applied in August, and became negative for irrigation applied in September. The best positive correlation between the soil water deficit factor (Ks) and yield occurred during weeks 12-14 from crop emergence, during the “milk” and “dough” growth stages. Yield was poorly correlated to stress during weeks 15 and 16, and the correlation became negative after week 17. Dividing the 150 mm allocation about evenly among July, August and September was a good strategy resulting in the highest yields in 2005, but not in 2006. Applying a larger proportion of the allocation in July was a good strategy during both years, and the opposite resulted when applying a large proportion of the allocation in September. The different results obtained between years indicate that flexible irrigation scheduling techniques should be adopted, rather than relying on fixed timing strategies.     

Can soil bunds increase the production of rain-fed lowland rice in south eastern Tanzania?

Rain-fed lowland rice is by far the most common production system in south eastern Tanzania. Rice is typically cultivated in river valleys and plains on diverse soil types although heavy soil types are preferred as they can retain moisture for a longer period. To assess the effects of soil bunds on the production of rain-fed lowland rice, the crop was cultivated in bunded and non-bunded farmers’ plots under the common agronomic practices in the region, in three successive seasons on Grumic Calcic Vertisols (Pellic). For the three seasons and for the two plot types, crop transpiration was simulated with the BUDGET soil water balance model by using the observed weather data, soil and crop parameters. Comparison between the observed yields and the simulated crop transpiration yielded an exponential relationship with a determination factor of 0.87 and an RMSE of 0.15 tonnes ha⁻¹. With the validated soil water balance model crop yields that can be expected in bunded and non-bunded fields were subsequently simulated for wet, normal and dry years and various environmental conditions. Yield comparison shows that soil bunds can appreciably increase the production of rain-fed lowland rice in south eastern Tanzania in three quarters of the years (wet and normal years) when the soil profile is slow draining (K_SAT equal to or less than 10 mm day⁻¹). In normal years a minimum yield increase of 30% may be expected on those soil types. In wet years and when the soil hardly drains (drainage class of 0–5 mm day⁻¹), the yield may even double. In dry years the yield increase will be most of the time less than 10% except for plots with a percolation rate of 0–5 mm day⁻¹.     

Nutrient management adaptation for dryland maize yields and water use efficiency to long-term rainfall variability in China

Rainfed crop production in northern China is constrained by low and variable rainfall, and by improper management practices. This study explored both the impact of long-term rainfall variability and the long-term effects of various combinations of maize stover, cattle manure and mineral fertiliser (NP) applications on maize (Zea mays L.) yields and water use efficiency (WUE) under reduced tillage practices, at Shouyang Dryland Farming Experimental Station in northern China from 1993 onwards. The experiment was set up according to an incomplete, optimal design, with 3 factors at five levels and 12 treatments including a control with two replications. Grain yields were greatly influenced by the amount of rain during the growing season, and by soil water at sowing. Annual mean grain yields ranged from 3 to 10 t ha⁻¹ and treatment mean yields from 4.2 to 7.2 t ha⁻¹. The WUE ranged from 40 in treatments with balanced nutrient inputs in dry (weather/or soil) years to 6.5 kg ha⁻¹ mm⁻¹ for the control treatments in wet years. The WUE averaged over the 15-year period ranged from 11 to 19 kg ha⁻¹ mm⁻¹. Balanced combination of stover (3000-6000 kg), manure (1500-6000 kg) and N fertiliser (105 kg) gave the highest yield and hence WUE. It is suggested that 100 kg N per ha should be a best choice, to be adapted according to availability of stover and manure. Possible management options under variable rainfall conditions to alleviate occurring moisture stress for crops must be tailored to the rainfall pattern. The potentials of split applications, targeted to the need of the growing crop (response nutrient management), should be explored to further improve grain yield and WUE.     

Detecting subsurface drainage systems and estimating drain spacing in intensively managed agricultural landscapes

Detailed location maps of tile drains in the Midwestern United States are generally not available, as the tile lines in these areas were laid more than 75 years ago. The objective of this study is to map individual tile drains and estimate drain spacing using a combination of GIS-based analysis of land cover, soil and topography data, and analysis of high resolution aerial photographs to within the Hoagland watershed in west-central Indiana. A decision tree classifier model was used to classify the watershed into potentially drained and undrained areas using land cover, soil drainage class, and surface slope data sets. After masking out the potential undrained areas from the aerial image, image processing techniques such as the first-difference horizontal and vertical edge enhance filters, and density slice classification were used to create a detailed tile location map of the watershed. Drain spacings in different parts of the watershed were estimated from the watershed tile line map. The decision tree identified 79% of the watershed as potential tile drained area while the image processing techniques predicted artificial subsurface drainage in approximately 50% of the Hoagland watershed. Drain spacing inferred from classified aerial image vary between 17 and 80 m. Comparison of estimated tile drained areas from aerial image analysis shows a close agreement with estimated tile drained areas from previous studies (50% versus 46% drained area) which were based on GIS analysis and National Resource Inventory survey. Due to lack of sufficient field data, the results from this analysis could not be validated with observed tile line locations. In general, the techniques used for mapping tile lines gave reasonable results and are useful to detect drainage extent from aerial image in large areas. These techniques, however, do not yield precise maps of the systems for individual fields and may not accurately estimate the extent of tile drainage in the presence of crop residue in agricultural fields and/or existence of other spatial features with similar spectral response as tile drains.     

Evaluation of DRAINMOD using saturated hydraulic conductivity estimated by a pedotransfer function model

Direct measurement of soil saturated hydraulic conductivity (K_s) is time-consuming and therefore costly. The ROSETTA pedotransfer function model is able to estimate K_s from soil textural data, bulk density and one or two water retention points. This study evaluated the feasibility of running the DRAINMOD field-scale hydrological model with K_s input produced using ROSETTA. A hierarchical approach was adopted to estimate K_s using ROSETTA, with four limited-more extended sets of soil information used as inputs: USDA textural class (H1); texture (H2); texture and bulk density (H3); texture, bulk density, water retention at −33 kPa (θ_33 kPa) and −1500 kPa (θ_1500 kPa) (H4). ROSETTA-estimated K_s values from these four groups (H1-H4) were used in DRAINMOD to simulate drain outflows during a 4-year period from a conventional drainage plot (CD) and two controlled drainage plots (CWT1 and CWT2) located in south-east Sweden. The DRAINMOD results using ROSETTA-estimated K_s values were compared with observed values and with model results using laboratory-measured K_s values (H0). Deviations in simulated drainage outflow (D), infiltration (F) and evapotranspiration (ET) resulting from the use of ROSETTA-estimated rather than laboratory-measured K_s values were evaluated. During the study period, statistical comparisons showed good agreement on a monthly basis between observed and DRAINMOD-simulated drainage rates using five soil datasets (H0, H1, H2, H3 and H4). The monthly mean absolute error (MAE) ranged from 0.57 to 0.82 cm for CD, 0.38 to 0.41 cm for CWT1, and 0.15 to 0.22 cm for CWT2. On a monthly basis, the modified coefficient efficiency (E′) values were in the range of 0.62 to 0.74 for CD, 0.72 to 0.74 for CWT1, and 0.79 to 0.86 for CWT2. The modified index of agreement (d′) for monthly predictions ranged from 0.80 to 0.86 cm for CD, 0.87 to 0.88 cm for CWT1, and 0.89 to 0.93 cm for CWT2. The absolute values of the percent-normalised error (NE) on an overall basis when using ROSETTA-estimated rather than laboratory-measured K_s values were less than 3% in E, less than 1% in F, and less than 15% in D. The results suggest that ROSETTA-estimated K_s values can be used in DRAINMOD to simulate drainage outflows as accurately as laboratory-measured K_s values (H0) in coarse-textured soils.