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.     

Using vegetation indices from satellite remote sensing to assess corn and soybean response to controlled tile drainage

Controlled tile drainage (CTD) is a management practice designed to retain water and nutrients in the field for crop use. CTD has shown promise for improving water quality and augmenting crop yields but findings are often restricted to field and plot scales. Remote sensing is one of the alternatives to evaluate crop responsiveness to CTD at large spatial scales. This study compared normalized and green normalized difference vegetation indices (NDVI and GNDVI) for corn (Zea mays L.) and soybean (Glycine max L.) among CTD and uncontrolled tile drainage (UCTD) fields in a ∼950 ha experimental watershed setting in Ontario, Canada from 2005 to 2008. The indices were derived from Landsat-5 and SPOT-4 satellite imagery. Log-transformed NDVI and GNDVI for soybean (R3-R6 growth stage) and corn (VT to R5-R6 growth stage) crops were higher significantly (p ≤ 0.05) for CTD, relative to UCTD for 50% (soybean) and 72% (corn) of both the log-transformed NDVI and GNDVI image acquisitions compared; only 17% and 13% were significant (p ≤ 0.05) in the reverse direction (UCTD > CTD). Log-transformed NDVI and GNDVI standard errors for CTD, relative to UCTD fields, were lower for 65% of the significant corn and 71% of the significant soybean NDVI and GNDVI comparisons for the growth stages noted above. This finding suggested overall more uniform crop growth for CTD fields relative to UCTD fields. Observed yields from a subset of commonly managed CTD and UCTD fields in the study area were not significantly different from each other (p > 0.05) with respect to tile drainage management practice; however, 87% of these paired yield comparisons indicated that CTD mean corn/soybean grain yields were greater than or equal to those for UCTD. On average, CTD observed corn and soybean grain yields were 3% and 4%, respectively, greater than those from UCTD. From observed yield and NDVI and GNDVI observations, vegetation indices vs. yield linear regression models were developed to predict grain yields over a broader land base in the experimental watershed area. Here, predicted mean yields were 0.1-11% higher for CTD corn and −5% to 4% higher for CTD soybean, relative to UCTD crops; but results varied between manured and non-manured fertilizer practices. Eighty-nine percent of the standard deviations for these yield predictions were lower for CTD relative to UCTD. The results of this study indicate that at a minimum, CTD did not adversely impact corn and soybean grain yields over the time span and field environments of the study, and based on the weight of evidence presented here, CTD shows general promise for augmenting crop performance. Finally, remote sensing derived vegetation indices such as NDVI and GNDVI can be used to assess the impact of agricultural drainage management practices on crop response and production properties.     

Modeling the impact of alternative drainage practices in the northern Corn-belt with DRAINMOD-NII

The hydrologic and water quality impacts of subsurface drainage design and management practices are being investigated through field and simulation studies throughout the northern Corn-belt. Six years of data from an ongoing field study in south central Minnesota (Sands et al., 2008) were used to support a modeling effort with DRAINMOD-NII to investigate: (1) the performance of the model in a region where soils are subject to seasonal freeze-thaw and (2) the long-term hydrologic and water quality characteristics of conventional and alternative subsurface drainage practices. Post-calibration model prediction and efficiency were deemed satisfactory using standard model performance criteria. Prediction errors were primarily associated with early spring snowmelt hydrology and were attributed to the methods used for simulating snow accumulation and melting processes, in addition to potential sublimation effects on ET estimates. Long-term simulations with DRAINMOD-NII indicated that drainage design and/or management practices proposed as alternatives to conventional design may offer opportunities to reduce nitrate (NO₃)-nitrogen losses without significantly decreasing (and in some cases, increasing) crop yields for a Webster silty clay loam soil at Waseca, Minnesota. The simulation study indicated that both shallow drainage and controlled drainage may reduce annual drainage discharge and NO₃-nitrogen losses by 20-30%, while impacting crop yields from −3% (yield decrease) to 2%, depending on lateral drain spacing. The practice of increasing drainage intensity (decreasing drain spacing) beyond recommended values appears to not significantly affect crop yield but may substantially increase drainage discharge and nitrate-nitrogen losses to surface waters.     

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.     

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.     

Predicting the effects of drainage systems on corn yields

Stress day index (SDI) models were incorporated in the water management simulation model, DRAINMOD, to quantify the effect of soil water stresses on corn yields. The effects of a combination of excessive and deficient soil water conditions were approximated by a simple first-order crop response model, YR = YRw × YRd, where YR is the overall relative yield, and YRw and YRd are the relative yields due to excessive and deficient soil water conditions, respectively.The accuracy of the modified water management model was evaluated by comparing predicted and measured corn yields for 16 plot years of experimental data on the Tidewater Research Station near Plymouth, NC. The predicted and measured results were in good agreement with the model describing 63% of the variation in yields for the 12-year period.Use of the modified water management model was demonstrated by simulating the performance of several drainage system designs for a Portsmouth sandy loam soil. The results of the simulation show that a maximum long-term relative yield of 80% of the potential corn yield can be obtained with a drain spacing of 40 m or less with good surface drainage. Higher yields could not be obtained without irrigation to reduce deficit soil water conditions. The response of long-term average corn yields to surface drainage varies inversely with the intensity of subsurface drainage. The 25-year average yield for 100 m spacing was only 47% of the potential yield when the surface drainage was poor as compared to 61% of potential yield for good surface drainage.     

Long-term water balances in La Violada Irrigation District (Spain): II. Analysis of irrigation performance

The analysis of long-term irrigation performance series is a valuable tool to improve irrigation management and efficiency. This work focuses in the assessment of irrigation performance indices along years 1995-2008, and the cause-effect relationships with irrigation modernization works taking place in the 4000 ha surface-irrigated La Violada Irrigation District (VID). Irrigation management was poor, as shown by the low mean seasonal irrigation consumptive use coefficient (ICUC = 51%) and the high relative water deficit (RWD = 20%) and drainage fraction (DRF = 54%). April had the poorest irrigation performance because corn (with low water demand in this month) was irrigated to promote its emergence, whereas winter grains (with high water demands in this month) were not fully irrigated in water-scarce years. Corn, highly sensitive to water stress, was the crop with best irrigation performance because it was preferentially irrigated to minimize yield losses. The construction of a new elevated canal that decreased seepage and drainage fractions, the entrance in operation of six internal reservoirs that would increase irrigation scheduling flexibility, and the on-going transformation from surface to sprinkler irrigation systems are critical changes in VID that should lead to improved ICUC, lower RWD and lower DRF. The implications of these modernization works on the conservation of water quantity and quality within and outside VID is further discussed.     

Distributed agro-hydrological modeling with SWAP to improve water and salt management of the Voshmgir Irrigation and Drainage Network in Northern Iran

The agro-hydrological model SWAP was used in a distributed manner to quantify irrigation water management effects on the water and salt balances of the Voshmgir Network of North Iran during the agricultural year 2006-2007. Field experiments, satellite images and geographical data were processed into input data for 10 uniform simulation areas. As simulated mean annual drainage water (312 mm) of the entire area was only 14% smaller than measured (356 mm), its distribution over the drainage units was well reproduced, and simulated and measured groundwater levels agreed well. Currently, water management leads to excessive irrigation (621-1436 mm year⁻¹), and leaching as well as high salinity of shallow groundwater are responsible for large amounts of drainage water (25-59%) and salts (44-752 mg cm⁻²). Focused water management can decrease mean drainage water (22-48%) and salts (30-49%), compared with current water management without adverse effects on relative transpiration and root zone salinity.     

DRAINMOD-S: Water management model for irrigated arid lands,crop yield and applications

The primary objective of an agriculture water management system is to provide crop needs to sustain high yields. Another objective of equal or greater importance in some regions is to reduce agriculture impacts on surface and groundwater quality. Kandil et al. (1992) modified the water management model DRAINMOD to predict soil salinity as affected by irrigation water quality and drainage system design. The objectives of this study are to incorporate an algorithm to quantify the effects of stresses due to soil salinity on crop yields and to demonstrate the applications of the model. DRAINMOD-S, is capable of predicting the long-term effects of different irrigation and drainage practices on crop yields. The overall crop function in the model includes the effects of stresses caused by excessive soil water conditions (waterlogging), soil water-deficits, salinity, and planting delays. Three irrigation strategies and six drain spacings were considered for all crops. In the first irrigation strategy, the irrigation amounts were equal to evapotranspiration requirements by the crops, with the addition of a 10 cm depth of water for leaching applied during each growing season. In the second strategy, the leaching depth (10 cm) was applied before the growing season. In the third strategy, a leaching depth of 15 cm was applied before the growing season for each crop. Another strategy (4th) with more leaching was considered for bean which is the crop most sensitive to salinity. In the fourth strategy, 14 days intervals were used instead of 7 and leaching irrigations were applied: 15 cm before the growing season and 10 cm at the middle of the growing season for bean. The objective function for these simulations was crop yield. Soil water conditions and soil salinity were continuously simulated for a crop rotation of bean, cotton, maize, soybean, and wheat over a 19 years period. Yields of individual crops were predicted for each growing season. Results showed that the third irrigation strategy resulted in the highest yields for cotton, maize, soybean and wheat. Highest yields for bean were obtained by the fourth irrigation strategy. Results are also presented on the effects of drain depth and spacing on yields. DRAINMOD-S is written in Fortran and requires a PC with math-coprocessor. It was concluded that DRAINMOD-S is a useful tool for design and evaluation of irrigation and drainage systems in irrigated arid lands.     

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.     

Integrated effect of transplanting date, cultivar and irrigation on yield, water saving and water productivity of rice (Oryza sativa L.) in Indian Punjab: Field and simulation study

Individual effect of different field scale management interventions for water saving in rice viz. changing date of transplanting, cultivar and irrigation schedule on yield, water saving and water productivity is well documented in the literature. However, little is known about their integrated effect. To study that, field experimentation and modeling approach was used. Field experiments were conducted for 2 years (2006 and 2007) at Punjab Agricultural University Farm, Ludhiana on a deep alluvial loamy sand Typic Ustipsamment soils developed under hyper-thermic regime. Treatments included three dates of transplanting (25 May, 10 June and 25 June), two cultivars (PR 118 inbred and RH 257 hybrid) and two irrigation schedules (2-days drainage period and at soil water suction of 16 kPa). The model used was CropSyst, which has already been calibrated for growth (periodic biomass and LAI) of rice and soil water content in two independent experiments. The main findings of the field and simulation studies conducted are compared to any individual, integrated management of transplanting date, cultivar and irrigation, sustained yield (6.3-7.5 t ha⁻¹) and saved substantial amount of water in rice. For example, with two management interventions, i.e. shifting of transplanting date to lower evaporative demand (from 5 May to 25 June) concomitant with growing of short duration hybrid variety (90 days from transplanting to harvest), the total real water saving (wet saving) through reduction in evapotranspiration (ET) was 140 mm, which was almost double than managing the single, i.e. 66 mm by shifting transplanting or 71 mm by growing short duration hybrid variety. Shifting the transplanting date saved water through reduction in soil water evaporation component while growing of short duration variety through reduction in both evaporation and transpiration components of water balance. Managing irrigation water schedule based on soil water suction of 16 kPa at 15-20 cm soil depth, compared to 2-day drainage, did not save water in real (wet saving), however, it resulted into apparent water saving (dry saving). The real crop water productivity (marketable yield/ET) was more by 17% in 25th June transplanted rice than 25th May, 23% in short duration variety than long and 2% in irrigation treatment of 16 kPa soil water suction than 2-days drainage. The corresponding values for the apparent crop water productivity (marketable yield/irrigation water applied) were 16, 20 and 50%, respectively. Pooled experimental data of 2 years showed that with managing irrigation scheduling based on soil water suction of 16 kPa at 15-20 cm soil depth, though 700 mm irrigation water was saved but the associated yield was reduced by 277 kg ha⁻¹.     

Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia

Yield constraint analysis for rainfed rice at a research station gives insight into the relative role of occurring yield-limiting factors. However, soil nutrient status and water conditions along toposequences in rainfed farmers’ fields may differ from those at the research station. Therefore, yield constraints need to be analyzed in farmers’ fields in order to design management strategies to increase yield and yield stability.We applied production ecological concepts to analyze yield-limiting factors (water, N) on rice yields along toposequences in farmers’ fields using data from on-farm experiments conducted in 2000-2002 in Indonesia. Potential, water-limited, and N-limited yields were simulated using the ORYZA2000 crop growth model. Farmers’ fields showed large spatial and temporal variation in hydrology (354-1235 mm seasonal rainfall, −150 to 50 cm field-water depth) and fertilizer doses (76-166 N, 0-45 P, and 0-51 kg K ha⁻¹). Farmers’ yields ranged from 0.32 to 5.88 Mg ha⁻¹. The range in yield gap caused by water limitations was 0-28% and that caused by N limitations 35-63%, with large temporal and spatial variability.The relative limitations of water and N in farmers’ fields varied strongly among villages in rainfed rice areas and toposequence positions, with yield gaps due to water and N at the top and upper middle positions higher than at the lower middle and bottom toposequence positions, and yield gaps in late wet seasons higher than those in early wet seasons. Management options (e.g. crop establishment dates, shortening turnaround time, using varieties with shorter duration, supplemental irrigation) to help the late-season crop escape, or minimize the negative effects of, late-season droughts and supplying adequate N-fertilizer are important for increasing yield in rainfed lowland rice in Indonesia. More N-fertilizer should be given to upper toposequence positions than to lower positions because the former had a lower indigenous nutrient supply and hence a better response to N-fertilizer inputs. Systems approaches using production ecological concepts can be applied in yield constraint analysis for indentifying management strategies to increase yield and yield stability in farmers’ fields in other rainfed lowland areas.     

Simulation of nitrate leaching under irrigated maize on sandy soil in desert oasis in Inner Mongolia, China

Water scarcity and nitrate contamination in groundwater are serious problems in desert oases in Northwest China. Field and ¹⁵N microplot experiments with traditional and improved water and nitrogen management were conducted in a desert oasis in Inner Mongolia Autonomous Region. Water movement, nitrogen transport and crop growth were simulated by the soil-plant system with water and solute transport model (SPWS). The model simulation results, including the water content and nitrate concentration in the soil profile, leaf area index, dry matter weight, crop N uptake and grain yield, were all in good agreement with the field measurements. The water and nitrogen use efficiency of the improved treatment were better than those of the traditional treatment. The water and nitrogen use efficiency under the traditional treatment were 2.0 kg m⁻³ and 21 kg kg⁻¹, respectively, while under the improved treatment, they were 2.2 kg m⁻³ and 26 kg kg⁻¹, respectively. Water drainage accounted for 24-35% of total water input (rainfall and irrigation) for the two treatments. Nitrogen loss by ammonia volatilization and denitrification was less than 5% of the total N input (including the N comes from irrigation). However, 32-61% of total nitrogen input was lost through nitrate leaching, which agreed with the ¹⁵N isotopic result. It is impetrative to improve the water and nitrogen management in the desert oasis.     

Simulation of nitrate-N movement in southern Ontario,Canada with DRAINMOD-N

DRAINMOD-N, a mathematical model to predict nitrate-N concentrations in surface runoff and drain outflows from subsurface-drained farmlands, has been tested against field data collected in southern Ontario. The data was collected in a corn field from 16 conventional drainage and subirrigation plots in Woodslee, Ontario, from 1992 to 1994. The model performance was evaluated by comparing the observed and simulated nitrate-N concentrations in surface runoff and drain outflows. A precise calculation of water-table depth is an essential prerequisite for a model to obtain a proper prediction of nitrate-N movement. For the simulation of water-table depth, the lowest root mean square error and the highest correlation coefficient of linear regression were 173 mm and 0.51 for the subirrigation plots; and 178 mm and 0.84 for the subsurface drainage plots. Therefore, the performance of DRAINMOD-N for soil hydrologic simulations was satisfactory and it could be used for assessing nitrogen fate and transport. For the simulation of nitrate-N losses in the subirrigation plots, the lowest root mean square error and the highest correlation coefficient of linear regression were 0.74 kg/ha and 0.98 for surface runoff; and 6.53 kg/ha and 0.91 for drain outflow. For the simulation in the subsurface drainage plots, the lowest root mean square error and the highest correlation coefficient of linear regression were 0.70 kg/ha and 0.96 for surface runoff; and 6.91 kg/ha and 0.92 for drain outflow. The results show that DRAINMOD-N can perform satisfactory simulation of soil hydrology and nitrate-N losses in surface runoff under various water-table management practices. The model can, therefore, be used to evaluate different water pollution scenarios and help in the development and testing of various pollution control strategies for fields in cold weather such as that in southern Canada.     

Corn yield responses under crop evapotranspiration-based irrigation management

Improving irrigation water management is becoming important to produce a profitable crop in South Texas as the water supplies shrink. This study was conducted to investigate grain yield responses of corn (Zea mays) under irrigation management based on crop evapotranspiration (ET_C) as well as a possibility to monitor plant water deficiencies using some of physiological and environmental factors. Three commercial corn cultivars were grown in a center-pivot-irrigated field with low energy precision application (LEPA) at Texas AgriLife Research Center in Uvalde, TX from 2002 to 2004. The field was treated with conventional and reduced tillage practices and irrigation regimes of 100%, 75%, and 50% ET_C. Grain yield was increased as irrigation increased. There were significant differences between 100% and 50% ET_C in volumetric water content (θ), leaf relative water content (RWC), and canopy temperature (T_C). It is considered that irrigation management of corn at 75% ET_C is feasible with 10% reduction of grain yield and with increased water use efficiency (WUE). The greatest WUE (1.6 g m⁻² mm⁻¹) achieved at 456 mm of water input while grain yield plateaued at less than 600 mm. The result demonstrates that ET_C-based irrigation can be one of the efficient water delivery schemes. The results also demonstrate that grain yield reduction of corn is qualitatively describable using the variables of RWC and T_C. Therefore, it appears that water status can be monitored with measurement of the variables, promising future development of real-time irrigation scheduling.     

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.     

Effects of controlled drainage on N and P losses and N dynamics in a loamy sand with spring crops

The effects of controlled drainage on N and P losses from soil were examined in a 4-year field drainage experiment on a loamy sand in Southern Sweden. Of the three plots (0.2 ha each), one was drained by conventional subsurface drainage (CD), and two by controlled drainage (CWT1 and CWT2). The groundwater level in the CWT plots was naturally drained to at least 70 cm below the soil surface during the vegetation period between early spring and harvest but allowed to rise to 20 cm below the soil surface during the rest of the year. Measurements of precipitation, drain outflow, weir depths and air and soil temperatures were carried out hourly. Groundwater levels were measured and samples of drain outflow for analyses were collected twice a month. Mineral N contents in soil were measured three times a year and grain yields and N uptake in crops after harvest.     

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.     

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.     

A study of root water uptake of crops indicated by hydrogen and oxygen stable isotopes: A case in Shanxi Province, China

Mechanisms of crop root water uptake play an important role in agricultural water management. In this study, stable isotopes were used to understand root water uptake patterns for the main crops (summer corn and cotton) in Shanxi Province, China. Precipitation, irrigation water, soil water, groundwater and stem water were sampled for stable isotopes analyses, and supported by hydrological observations. Both direct inference of hydrogen and oxygen isotopes between stem water and the soil water profile, and multiple-source mass balance assessment were applied to estimate the main depths of root water uptake of crops in different growing seasons. The results show that summer corn and cotton have different root water uptake patterns: summer corn mainly uses the shallow soil water from 0 to 20 cm layer (96-99%) in jointing stage and extending to 20-50 cm (58-85%) in flowering stage, then 0-20 cm (69-76%) again in full ripe stage. In contrast, the main depth of root water uptake of cotton gradually increases during the whole growth stage: from 0 to 20 cm (27-49%) in seedling stage, 20-50 cm (79-84%) in bud stage, 50-90 cm (30-92%) in blooming stage and >90 cm (69-92%) in boll open stage.