Sugarcane transpiration with shallow water-table: sap flow measurements and modelling

The most common sugarcane variety in the Gharb plain of Morocco (CP 66-345 variety) was grown in a lysimeter in the laboratory. It developed during 6 months with a water-table at 0.7 m below the soil surface. The water-table was then successively maintained with a Mariotte bottle at 0.45, 0.2 and 0.05 m from the soil surface for 21, 31 and 24 days, respectively. Transpiration was measured by Dynamax sap flow sensors. Soil water pressure heads were measured at six different depths; soil hydraulic properties and root density profile were also determined. No transpiration reduction was observed with soil waterlogging. Two different models were used to predict the pattern of root water uptake (RWU) with water-table at 0.45 m below the soil surface. These two models are based on a RWU function used as sink term in the Richards equation. The first model, HYDRUS-2D (Simunek et al., 1996), is based on the α-model RWU (Feddes et al., 1978a) which depends on a reduction function varying according to the soil water pressure head and on the root density. The second model, SIC (Breitkopf and Touzot, 1992) is based on the h_r-model RWU (Whisler and Millington, 1968, Feddes et al., 1974). It is proportional to the difference between soil and root pressure heads, to unsaturated hydraulic conductivity and to root density. Calculated soil water flows from pressure head measurements are compared to predicted pressure heads by the two models. These predictions compare well with the measured values and show that sugarcane roots mainly absorbed water in the water-table. However, while goods predictions were obtained using the actual root density profile with the h_r-model, it was necessary to modify this profile to obtain proper results using the α-model.     

Spatial analysis of soil surface hydraulic properties: Is infiltration method dependent?

The management of irrigated agricultural fields requires reliable information about soil hydraulic properties and their spatio-temporal variability. The spatial variability of saturated hydraulic conductivity, K_s and the alpha-parameter α_vG-2007 of the van Genuchten equation was reviewed on an agricultural loamy soil after a 17-year period of repeated conventional agricultural practices for tillage and planting. The Beerkan infiltration method and its algorithm BEST were used to characterize the soil through the van Genuchten and Brooks and Corey equations. Forty field measurements were made at each node of a 6 m × 7.5 m grid. The soil hydraulic properties and their spatial structure were compared to those recorded in 1990 on the same field soil, through the exponential form of the soil hydraulic conductivity given by the Gardner equation, using the Guelph Pressure Infiltrometer technique. No significant differences in the results obtained in 1990 and 2007 were observed for either particle-size distribution or dry bulk density. The mean value of α_vG-2007 was found to be identical to that of α_G-1990, while that of K_s-2007 was significantly smaller than that of K_s-1990. In contrast to the Gardner equation, the van Genuchten/Brooks and Corey expression was found to be more representative of a well-graded particle-size distribution of a loamy soil. The geostatistical analysis showed the two parameters, K_s and α_vG-2007, were autocorrelated up to about 30 and 21 m, respectively, as well as spatially positively correlated within a range of 30 m. Despite the difference in the mean values of K_s between the two studies, the spatial structures were similar to those found in the 1990 experiment except for the covariance sign. The similarity in autocorrelation ranges indicate that the spatial analysis of soil hydraulic properties is independent of the infiltration methods (i.e., measurement of an infiltration flux) used in the two studies, while the difference in the covariance sign may be linked to the use of two different techniques of soil hydraulic parameterization. The covariance values found in the 2007 campaign indicates a positive relationship between the two parameters, K_s and α_vG-2007. The spatial correlations of soil hydraulic parameters appear to be temporally stabilized, at least within the agro-pedo-climatic context of the study. This may be attributed to the soil textural properties which remain constant in time and to the structural properties which are constantly renewed by the cyclic agricultural practices. However, further experiments are needed to strengthen this result.     

A distributed agro-hydrological model for irrigation water demand assessment

The actual irrigation water demand in a district in Sicily (Italy) was assessed by the spatially distributed agro-hydrological model SIMODIS (SImulation and Management of On-Demand Irrigation Systems). For each element with homogeneous crop and soil conditions, in which the considered area can be divided, the model numerically solves the one-dimensional water flow equation with vegetation parameters derived from Earth Observation data. In SIMODIS, the irrigation scheduling is set by means of two parameters: the threshold value of soil water pressure head in the root zone, h_m, and the fraction of soil water deficit to be re-filled, Δ. This study investigated the possibility of identifying a couple of irrigation parameters (h_m, Δ) which allowed to reproduce the actual irrigation water demand, given that the study area was adequately characterized with regard to the spatial distribution of the soil hydraulic properties and the vegetation conditions throughout the irrigation season. The spatial distribution of the soil and vegetation properties of the study area, covering an irrigation district of approximately 800 ha, was accurately characterized during the summer of 2002. The soil hydraulic properties were identified by an intensive undisturbed soil sampling, while the vegetation cover was characterized in terms of leaf area index, surface albedo and fractional soil cover by analysing multispectral LandSat TM imageries. Irrigation volumes were monitored at parcel scale.A reference scenario with h_m = −700 cm and Δ = 50% (corresponding to a mean actual to potential transpiration ratio of 0.95) allowed to reproduce the spatial and temporal distribution of the actual irrigation demand at the district scale. The spatial variability of the crop conditions in the considered area had much more influence to assess the irrigation water demand than the soil hydraulic spatial variability. The proposed approach showed that, under the agro-climatic conditions typical for the Mediterranean region, SIMODIS may be a valuable tool in managing irrigation to increase water productivity.     

Artificial neural network and time series models for predicting soil salt and water content

Volumetric water content of a silt loam soil (fluvo-aquic soil) in North China Plain was measured in situ by L-520 neutron probe (made in China) at three depths in the crop rootzone during a lysimeter experiment from 2001 to 2006. The electrical conductivity of the soil water (EC_sw) was measured by salinity sensors buried in the soil during the same period at 10, 20, 45 and 70 cm depth below soil surface. These data were used to test two mathematical procedures to predict water content and soil water salinity at depths of interest: all the available data were divided into training and testing datasets, then back propagation neural networks (BPNNs) were optimized by sensitivity analysis to minimizing the performance error, and then were finally used to predict soil water and EC_sw. In order to meet with the prerequisite of autoregressive integrated moving average (ARIMA) model, firstly, original soil water content and EC_sw time series were likewise transformed to obtain stationary series. Subsequently, the transformed time series were used to conduct analysis in frequency domain to obtain the parameters of the ARIMA models for the purposes of using the ARIMA model to predict soil water content and EC_sw. Based on the statistical parameters used to assess model performance, the BPNN model performed better in predicting the average water content than the ARIMA model: coefficient of determination (R²) = 0.8987, sum of squares error (SSE) = 0.000009, and mean absolute error (MAE) = 0.000967 for BPNN as compared to R² = 0.8867, SSE = 0.000043, MAE = 0.002211 for ARIMA. The BPNN model also performed better than the ARIMA model in predicting average EC_sw of soil profile. However, the ARIMA model performed better than the BPNN models in predicting soil water content at the depth of 20 cm and EC_sw at the depth of 10 cm below soil surface. Overall, the model developed by BPNN network showed its advantage of less parameter input, nonlinearity, simple model structure and good prediction of soil EC_sw and water content, and it gave an alternative method in forecasting soil water and salt dynamics to those based on deterministic models based on Richards’ equation and Darcy's law provided climatic, cropping patterns, salinity of the irrigation water and irrigation management are very similar from one year to the next.     

Analyzing soil soluble phosphorus transport with root-phosphorus-uptake applying an inverse method

Soil soluble phosphorus (P) transport with root-phosphorus-uptake (RPU) is a critical process for plant growth, cycling of P in soil-plant systems and environment protection. However, modeling soil soluble P transport is extremely challenging because it is difficult to measure the RPU distribution directly, especially in the field. In this study, an inverse method, which was utilized successfully to estimate the root-water-uptake (RWU) rate distribution by Zuo and Zhang (2002) and the source-sink term in the nitrate (NO⁻₃-N) transport equation by Shi et al. (2007), was applied to estimate the RPU rate distribution and analyze soil soluble P transport in the soil-plant systems. A soil column experiment (Exp. 1) and a field experiment (Exp. 2), respectively with winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) growth, were carried out to observe the dynamics of soil water and soluble P. Based on the experimental data in Exp. 1, the average RWU and RPU rate distributions during different irrigation periods were estimated using the inverse method. The relative errors of the total P extracted by wheat between the estimated and measured values during all periods were less than 10%. The estimated RPU rate distribution during the period of 10.5-15.5 days after planting (DAP) was used to optimize the dimensionless RPU factor δ to establish the RPU model (δ = 1.31), which helped to calculate the RPU rate distributions during other periods (from 16.5 to 57.5 DAP) in Exp. 1. The calculated RPU rate distributions were compared well with the estimated profiles by the inverse method, and the root mean squared error between them was less than 0.00005 mg cm⁻³ d⁻¹. Correspondingly, the calculated total P extracted by winter wheat was also comparable with the measured value, with the relative error less than 10%. Similarly, the procedures were employed for summer maize in Exp. 2. The estimated (using the inverse method) and calculated (through the RPU model with δ = 1.38) RPU rate distributions were in good agreement with the root mean squared error as less as 0.000031 mg cm⁻³ d⁻¹. According to the established RPU models (δ = 1.31 and 1.38 for Exps. 1 and 2, respectively), the distributions of soil water content and soluble P concentration were simulated, and compared well with the measured profiles, with the maximum root mean squared error of 0.0088 cm³ cm⁻³ and 0.0066 mg cm⁻³ in Exp. 1, and 0.023 cm³ cm⁻³ and 0.0015 mg cm⁻³ in Exp. 2, respectively. The inverse method should be effective and applicable for estimating the RPU rate distribution, establishing the RPU model and analyzing soil soluble P transport in soil-plant systems, either in laboratory or in the field.     

Antecedent water content effects on runoff and sediment yields from two Coastal Plain Ultisols

The highly weathered, low-carbon, intensively cropped, drought-prone Coastal Plain soils of Georgia are susceptible to runoff and soil loss, especially at certain times of the year when soil water contents are elevated. We quantified the effects of antecedent water content (AWC) on runoff (R) and sediment (E) losses from two loamy sands managed under conventional- (CT), strip- (ST), and/or no-till (NT) systems. Two AWC treatments were evaluated: field moist (FM) and pre-wet (PW), created with and without post pesticide application irrigations (∼12 mm of water added with the rainfall simulated over 30 min) for incorporation. Treatments (5) evaluated were: CT + FM, CT + PW, ST + FM, ST + PW, and NT + PW. Field plots, each 2-m × -3 m, were established on each treatment. Each 6-m² field plot received simulated rainfall at a variable rainfall intensity (I_v) pattern for 70 min (site 1) or a constant rainfall intensity (I_c) pattern for 60 min (site 2; I_c = 50.8 mm h⁻¹). Adding ∼12 mm of water as herbicide incorporation increased AWCs of the 0-2 (3-9-fold) and 2-15 (23-117%) cm soil depths of PW plots compared to existing field moist soil conditions. Increase in AWC increased R (as much as 60%) and maximum R rates (as much as 62%), and decreased E (at least 59%) and maximum E rates (as much as 2.1-fold) for corresponding tillage treatments. Compared to CT plots, ST and NT plots decreased R (at least 2.6-fold) and maximum R rates (as much as 3-fold), and decreased E (at least 2.7-fold) and maximum E rates (at least 3.2-fold). Runoff curves for pre-wetted CT and ST plots were always higher than corresponding FM curves, whereas E curves for field moist CT and ST plots were always higher than corresponding PW curves. Changes in AWC and tillage affected detachment and transport processes controlling runoff and sediment yields. A more accurate measure of rainfall partitioning and detachment and transport processes affecting R and E losses was obtained when commonly occurring field conditions (increased AWC with irrigation; I_v pattern derived from natural rainfall; commonly used tillage systems) were created and evaluated.     

Impacts of climate variability on reference evapotranspiration over 58 years in the Haihe river basin of north China

Physically, evaporative demand is driven by net radiation (R_n), vapour pressure (e_a), wind speed (u₂), and air temperature (T_a), each of which changes over time. By analyzing temporal variations in reference evapotranspiration (ET₀), improved understanding of the impacts of climate change on hydrological processes can be obtained. In this study, variations in ET₀ over 58 years (1950-2007) at 34 stations in the Haihe river basin of China were analyzed. ET₀ was calculated by the FAO Penman-Monteith formula. Calculation of Kendall rank coefficient was done by analyzing the annual and seasonal trends in ET₀ derived from its dependent climate variables. Inverse distance weighting (IDW) was used to analyze the spatial variation in annual and seasonal ET₀, and in each climate variable. An attribution analysis was performed to quantify the contribution of each input variable to ET₀ variation. The results showed that ET₀ gradually decreased in the whole basin over the 58 years at a rate of −1.0 mm yr⁻², at the same time, R_n, u₂ and precipitation also decreased. Changes in ET₀ were attributed to the variations in net radiation (−0.9 mm yr⁻²), vapour pressure (−0.5 mm yr⁻²), wind speed (−1.3 mm yr⁻²) and air temperature (1.7 mm yr⁻²). Looking at all data on a month by month basis, we found that T_a had a positive effect on dET₀/dt (the derivative of reference evapotranspiration to time) and R_n and u₂ had negative effects on dET₀/dt. While changes in air temperature were found to produce a large increase in dET₀/dt, changes in other key variables each reduced rates, resulting in an overall negative trend in dET₀/dt.     

Performance evaluation and calibration of soil water content and potential sensors for agricultural soils in eastern Colorado

This study evaluated the performance of three soil water content sensors (CS616/625, Campbell Scientific, Inc., Logan, UT; TDT, Acclima, Inc., Meridian, ID; 5TE, Decagon Devices, Inc., Pullman, WA) and a soil water potential sensor (Watermark 200SS, Irrometer Company, Inc., Riverside, CA) in laboratory and field conditions. Soil water content/potential values measured by the sensors were compared with corresponding volumetric water content (θ_v, m³ m⁻³) values derived from gravimetric samples, ranging approximately from the permanent wilting point (PWP) to field capacity (FC) volumetric water contents. Under laboratory and field conditions, the factory-based calibrations of θ_v did not consistently achieve the required accuracy for any sensor in the sandy clay loam, loamy sand, and clay loam soils of eastern Colorado. Salt (calcium chloride dihydrate) added to the soils in the laboratory caused the CS616, TDT, and 5TE sensors to experience errors in their volumetric water content readings with increased bulk soil electrical conductivity (EC; dS m⁻¹). Results from field tests in sandy clay loam and loamy sand soils indicated that a linear calibration (equations provided) for the TDT, CS616 and 5TE sensors (and a logarithmic calibration for the Watermark sensors) could reduce the errors of the factory calibration of θ_v to less than 0.02 ± 0.035 m³ m⁻³. Furthermore, the performance evaluation tests confirmed that each individual sensor needed a unique calibration equation for every soil type and location in the field. In addition, the calibrated van Genuchten (1980) equation was as accurate as the calibrated logarithmic equation and can be used to convert soil water potential (kPa) to volumetric soil water content (m³ m⁻³). Finally, analysis of the θ_v field data indicated that the CS616, 5TE and Watermark sensor readings were influenced by diurnal fluctuations in soil temperature, while the TDT was not influenced. Therefore, it is recommended that the soil temperature be considered in the calibration process of the CS616, 5TE, and Watermark sensors. Further research will be aimed towards determining the need of sensor calibration for every agricultural season.     

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.     

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.     

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.     

Soil salinity related to physical soil characteristics and irrigation management in four Mediterranean irrigation districts

Irrigated agriculture is threatened by soil salinity in numerous arid and semiarid areas of the Mediterranean basin. The objective of this work was to quantify soil salinity through electromagnetic induction (EMI) techniques and relate it to the physical characteristics and irrigation management of four Mediterranean irrigation districts located in Morocco, Spain, Tunisia and Turkey. The volume and salinity of the main water inputs (irrigation and precipitation) and outputs (crop evapotranspiration and drainage) were measured or estimated in each district. Soil salinity (EC_e) maps were obtained through electromagnetic induction surveys (EC_a readings) and district-specific EC_a-EC_e calibrations. Gravimetric soil water content (WC) and soil saturation percentage (SP) were also measured in the soil calibration samples. The EC_a-EC_e calibration equations were highly significant (P < 0.001) in all districts. EC_a was not significantly correlated (P > 0.1) with WC, and was only significantly correlated (P < 0.1) with soil texture (estimated by SP) in Spain. Hence, EC_a mainly depended upon EC_e, so that the maps developed could be used effectively to assess soil salinity and its spatial variability. The surface-weighted average EC_e values were low to moderate, and ranked the districts in the order: Tunisia (3.4 dS m⁻¹) > Morocco (2.2 dS m⁻¹) > Spain (1.4 dS m⁻¹) > Turkey (0.45 dS m⁻¹). Soil salinity was mainly affected by irrigation water salinity and irrigation efficiency. Drainage water salinity at the exit of each district was mostly affected by soil salinity and irrigation efficiency, with values very high in Tunisia (9.0 dS m⁻¹), high in Spain (4.6 dS m⁻¹), moderate in Morocco (estimated at 2.6 dS m⁻¹), and low in Turkey (1.4 dS m⁻¹). Salt loads in drainage waters, calculated from their salinity (EC_dw) and volume (Q), were highest in Tunisia (very high Q and very high EC_dw), intermediate in Turkey (extremely high Q and low EC_dw) and lowest in Spain (very low Q and high EC_dw) (there were no Q data for Morocco). Reduction of these high drainage volumes through sound irrigation management would be the most efficient way to control the off-site salt-pollution caused by these Mediterranean irrigation districts.     

Effects of irrigation strategies and soils on field-grown potatoes: Gas exchange and xylem [ABA]

Gas exchange was measured in potatoes (cv. Folva) grown in lysimeters (4.32 m²) in coarse sand, loamy sand, and sandy loam and subjected to full (FI), deficit (DI), and partial root-zone drying (PRD) irrigation strategies. PRD and DI as water-saving irrigation treatments received 65% of FI and started after tuber bulking and lasted for six weeks until final harvest. Midday photosynthesis rate (A_n) and stomatal conductance (g_s) of fully irrigated (FI) plants were lowest in coarse sand and mean A_n of diurnal measurements in FI, PRD and DI tended to be lower in this soil as compared with the loamy sand and sandy loam. The results revealed that diurnal values of A_n and g_s in PRD and DI were consistently lower than FI without reaching significant differences in accordance with findings that xylem [ABA] in PRD was significantly higher than FI, and tended to be higher than in DI. Diurnal measurements showed that A_n reached peak values during mid-morning and midday, while g_s were highest during the morning. Intrinsic water use efficiency (A_n/g_s) correlated linearly well with the leaf to air vapor pressure deficit (VPD) and the slope of the line revealed the rate of A_n/g_s increase per each kPa increase in VPD, i.e. approximately 10 μmol mol⁻¹. Transpiration efficiency (A_n/T) of PRD was higher than DI, which shows slightly better efficient water use than DI. The slope of the linear relationship between transpiration efficiency and VPD decreased from −2.03 to −1.04 during the time course of the growing season, indicating the negative effect of leaf ageing on photosynthesis and thus on plant water use efficiency. This fact shows the possibility to save water during last growth stages through applying water-saving irrigations without much effect on transpiration efficiency.     

Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.)

A combined methodology of basal crop coefficient (K_cb) derived from vegetation indices (VI) obtained from satellite images and a daily soil water balance in the root zone of the crop was proposed to accurately estimate the daily grape crop coefficient and actual evapotranspiration. The modeled values were compared with field measurements of crop evapotranspiration (ET) using an energy balance eddy-covariance flux tower and adjusted for closure using the measured Bowen ratio. A linear relation between K_cb and VI for vineyard was obtained, K_cb = 1.44 × NDVI-0.10 and K_cb = 1.79 × SAVI-0.08. The correlation of the measured crop coefficient (K_c) and modeled (K_crf) exhibits a linear tendency, K_c = 0.96K_crf, r² = 0.67. Other derived parameters such as weekly K_c and daily and weekly ET show good consistency with measurements and higher coefficients of determination. The study of the soil water balance suggests the importance of soil water storage in grapes within the La Mancha region. These results validate the use of remote sensing as a tool for the estimation of evapotranspiration of irrigated wine grapes planted on trellis systems.     

Evapotranspiration components determined by sap flow and microlysimetry techniques of a vineyard in northwest China: Dynamics and influential factors

Large areas of vineyards have been established in recent years in arid region of northwest China, despite limited water resources. Water to support these vineyards is mainly supplied by irrigation. Accurate estimation of vineyard evapotranspiration (ET) can provide a scientific basis for developing irrigation management. Transpiration and soil evaporation, as two main components of ET, were measured separately in a vineyard in this region by heat balance sap flow system and micro-lysimeters during the growing season of 2009. Diurnal and seasonal dynamics of sap flow and its environmental controls were analyzed. Daily sap flow rate (SR_l) increased linearly with solar radiation (R_s), but showed an exponential increase to its maximum curve as a function of vapor pressure deficit (VPD). Residuals of the two regressions both depended on volumetric soil water content to a depth of 1.0 m (VWC). VWC also significantly influenced SR_l. The relationship of them could be expressed by a piecewise regression with the turnover point of VWC = 0.188 cm³ cm⁻³, which was ∼60% of the field capacity. Conversely, soil evaporation (E_s) increased exponentially with VWC. Thus, we recommended keeping VWC in such vineyards slightly above ∼60% of the field capacity to maintain transpiration while reducing soil evaporation. Vineyard transpiration (T_s) was scaled from sap flow by using leaf area (A_l) as it explained 60% of the spatial variability of sap flow. Vine transpiration was 202.0 mm during the period from April 28 to October 5; while that of E_s was 181.0 mm. The sum of these two components was very close to ET estimated by the Bowen ratio energy balance method (386.9 mm), demonstrating the applicability of sap flow for measuring grape water use in this region.     

Development and evaluation of integrated water and nitrogen model for maize

Maize (Zea mays L.) is an important food crop for irrigated regions in the world. Its growth and production may be estimated by different crop models in which various relationships between growth and environmental parameters are used. For simulation of maize growth and grain yield, a simulation model was developed (Maize Simulation Model, MSM). Dynamic flow of water, nitrogen (N) movement, and heat flow through the soil were simulated in unsteady state conditions by numerical analysis in soil depth of 0–1.8 m. Hourly potential evapotranspiration [ET_p(t)] for maize field was estimated directly by Penman–Monteith method. Hourly potential evaporation [E_p(t)] was estimated based on ET_p(t) and canopy shadow projection. Actual evaporation of soil surface was estimated based on its potential value, relative humidity of air, water pressure head and temperature at soil surface layer. Actual transpiration (T_a(t)) was estimated based on soil water content and root distribution at each soil layer. Hourly N uptake by plant was simulated by N mass flow and diffusion processes. Hourly top dry matter production (HDMA^j + 1, where j is number of hours after planting) was estimated by hourly corrected intercepted radiation (RSLT^j + 1) by plant leaves [determined from leaf area index (LAI^j + 1)] with air temperature, the maximum and minimum plant top N concentration and the amounts of nitrogen uptake. The value of LAI^j + 1 at each hour was estimated by the accumulated top dry matter production at previous hour using an empirical equation. Maize grain yield was estimated by a relationship between harvest index and seasonal plant top dry matter production. The model was calibrated using data obtained under field conditions by a line source sprinkler irrigation. When the values of water and nitrogen application were optimum, grain yield (moisture content of 15.5%) was 16.2 Mg ha⁻¹. Model was validated using two independent experimental data obtained from other experiments in the Badjgah (Fars province). The experimental results validated the proposed simulation model fairly well.     

Sensitivity analysis and field testing of the RISK-N model in the Central Valley of Chile

We present the results from a sensitivity analysis and a preliminary short-term, site-scale performance assessment of the analytical soil and groundwater nitrate transport RISK-N. The study was carried out in the Central Valley of Chile, on a 2.6 ha corn (Zea mays L.) field underlain by a shallow unconfined aquifer during the cropping season 2000–2001. Nitrogen levels in soils as well as NO₃⁻–N irrigation water and groundwater concentrations were monitored through the crop-growing period, the latter by a network of 16 monitoring wells. A sensitivity analysis shows that both the nitrate flux from the vadose zone and NO₃⁻–N groundwater concentration are mainly influenced by the initial soil nitrogen levels, water input, and soil porosity. Also, simulated groundwater NO₃⁻–N levels are sensitive to changes on the saturated zone denitrification constant. An additional analysis further reveals the significance of the latter parameter, in conjunction with the amount of applied nitrogen fertilizer. We obtained a good agreement between observed average and simulated values. While the model performs well when spatially averaged values are used (root mean square error, RMSE = 1.4 mg l⁻¹ of NO₃⁻–N), the prediction error increases (RMSE = 1.9 mg l⁻¹ of NO₃⁻–N) when the concentration in each well is considered. This fact could be explained by the time and space scale of the experiment and the characteristics of the RISK-N model. The model is easy to use and seems appropriate for mid- and long-term studies of nitrogen contamination in groundwater for agricultural conditions in the Central Valley of Chile and under limited field data availability conditions. However, it needs to be tested for longer periods and under different climatic conditions, soil types, and aquifer characteristics, before its range of applicability can be fully established and recognized.     

Effects of irrigation strategies and soils on field grown potatoes: Root distribution

Root distribution of field grown potatoes (cv. Folva) was studied in 4.32 m² lysimeters and subjected to full (FI), deficit (DI), and partial root-zone drying (PRD) irrigation strategies. Drip irrigation was applied for all irrigations. Irrigations were run in three different soils: coarse sand, loamy sand, and sandy loam. Irrigation treatments started after tuber bulking and lasted until final harvest with PRD and DI receiving 65% of FI. Potatoes irrigated with water-saving irrigation techniques (PRD and DI) did not show statistically different dry root mass and root length density (RLD, cm root per cm³ soil) compared with root development in fully irrigated (FI) potatoes. Highest RLD existed in the top 30-40 cm of the ridge below which it decreased sharply. The RLD was distributed homogenously along the ridge and furrow but heterogeneously across the ridge and furrow with highest root density in the furrow. Most roots accumulated in the surface layers of coarse sand as compared to the other soil types. In the deep soil profile (30-70 cm) a higher root density was found in loamy sand compared with the sandy loam and coarse sand. Approximately twice the amounts of roots were found below the furrows compared with the corresponding layers below the ridges. The RLD values in the soil profile of the ridges and the furrows followed the Gerwitz and Page model: RLD = α × exp(−β × z). The highest value of surface root density (α) and rate of change in density (β) was found in coarse sand while the lowest values of α and β were found in the sandy loam and loamy sand. The model estimated the effective rooting depth in coarse sand and sandy loam quite well but did slightly overestimate it in the loamy sand. Statistical analysis showed that one α and β value can be used for each soil irrespective of the irrigation treatment. Thus, the effective rooting depths corresponding to root length densities of 0.1 and 0.25 cm cm⁻³ for sandy loam, loamy sand, and coarse sand soils were 99, 141, and 94 cm, and 80, 115, and 78 cm, respectively, calculated from top of the ridge. The findings of this study can be used in practice for efficient use of water and nutrients in the field.     

Using the dual approach of FAO-56 for partitioning ET into soil and plant components for olive orchards in a semi-arid region

The main goal of this research was to evaluate the potential of the dual approach of FAO-56 for estimating actual crop evapotranspiration (AET) and its components (crop transpiration and soil evaporation) of an olive (Olea europaea L.) orchard in the semi-arid region of Tensift-basin (central of Morocco). Two years (2003 and 2004) of continuous measurements of AET with the eddy-covariance technique were used to test the performance of the model. The results showed that, by using the local values of basal crop coefficients, the approach simulates reasonably well AET over two growing seasons. The Root Mean Square Error (RMSE) between measured and simulated AET values during 2003 and 2004 were respectively about 0.54 and 0.71 mm per day. The basal crop coefficient (K_cb) value obtained for the olive orchard was similar in both seasons with an average of 0.54. This value was lower than that suggested by the FAO-56 (0.62). Similarly, the single approach of FAO-56 has been tested in the previous work (Er-Raki et al., 2008) over the same study site and it has been shown that this approach also simulates correctly AET when using the local crop coefficient and under no stress conditions.Since the dual approach predicts separately soil evaporation and plant transpiration, an attempt was made to compare the simulated components of AET with measurements obtained through a combination of eddy covariance and scaled-up sap flow measurements. The results showed that the model gives an acceptable estimate of plant transpiration and soil evaporation. The associated RMSE of plant transpiration and soil evaporation were 0.59 and 0.73 mm per day, respectively.Additionally, the irrigation efficiency was investigated by comparing the irrigation scheduling design used by the farmer to those recommended by the FAO model. It was found that although the amount of irrigation applied by the farmer (800 mm) during the growing season of olives was twice that recommended one by the FAO model (411 mm), the vegetation suffered from water stress during the summer. Such behaviour can be explained by inadequate distribution of irrigation. Consequently, the FAO model can be considered as a potentially useful tool for planning irrigation schedules on an operational basis.     

Modelling for maize irrigation scheduling using long term experimental data from Plovdiv region, Bulgaria

Independent historic datasets on irrigated maize, collected over seven years (1984-1990), were used to parameterize the irrigation scheduling model ISAREG. Experimental data were obtained under rainfed, deficit, and full irrigation conditions in an alluvial soil at Tsalapitsa, Plovdiv region, in the Thracian plain, Bulgaria. Crop coefficients and depletion fractions for no-stress were calibrated by minimizing the differences between observed and simulated soil water content. The calibration was performed using data from full irrigation and rainfed treatments while deficit irrigation treatments were used for validation. The modelling efficiency was high, 0.91 for the calibration and 0.89 for the validation. The resulting average absolute errors of the estimate for the soil water content were smaller than 0.01 cm³ cm⁻³. The model was also tested by comparing computed versus observed seasonal evapotranspiration. Results for dry years show a modelling efficiency of 0.96 but the model slightly underestimated evapotranspiration for other years. The yield response factor was derived from observed yield data of the hybrid variety H708 when relative evapotranspiration deficits were smaller than 0.5. The value K_y = 1.32 was obtained. The relative yield decreases predicted with this K_y value compared well with observed data. Results support the use of the ISAREG model for developing water saving irrigation schedules for the Thracian plain.