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.     

A global benchmark map of water productivity for rainfed and irrigated wheat

The growing pressure on fresh water resources demands that agriculture becomes more productive with its current water use. Increasing water productivity is an often cited solution, though the current levels of water productivity are not systematically mapped. A global map of water productivity helps to identify where water resources are productively used, and identifies places where improvements are possible. The WATPRO water productivity model for wheat, using remote sensing data products as input, was applied at a global scale with global data sets of the NDVI and surface albedo to benchmark water productivity of wheat for the beginning of this millennium. Time profiles of the NDVI were used to determine the time frame from crop establishment to harvest on a pixel basis, which was considered the modelling period. It was found that water productivity varies from approximately 0.2 to 1.8 kg of harvestable wheat per cubic metre of water consumed. From the 10 largest producers of wheat, France and Germany score the highest country average water productivity of 1.42 and 1.35 kg m⁻³, respectively. The results were compared with modelling information by Liu et al. (2007) who applied the GEPIC model at a global scale to map water productivity, and by Chapagain and Hoekstra (2004) who used FAO statistics to determine water productivity per country. A comparison with Liu et al. showed a good correlation for most countries, but the correlation with the results by Chapagain and Hoekstra was less obvious. The global patterns of the water productivity map were compared with global data sets of precipitation and reference evapotranspiration to determine the impact of climate and of water availability reflected by precipitation. It appears that the highest levels of water productivity are to be expected in temperate climates with high precipitation. Due to its non-linear relationship with precipitation, it is expected that large gains in water productivity can be made with in situ rain water harvesting or supplemental irrigation in dry areas with low seasonal precipitation. A full understanding of the spatial patterns by country or river basin will support decisions on where to invest and what measures to take to make agriculture more water productive.     

SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems

A methodology has been developed to quantify spatial variation of crop yield, evapotranspiration (ET) and water productivity (WP_ET) using the SEBAL algorithm and high and low resolution satellite images. SEBAL-based ET estimates were validated over an irrigated, wheat dominated area in the Yaqui Valley, Mexico and proved to be accurate (8.8% difference for 110 days). Estimated average wheat yields in Yaqui Valley of 5.5 t ha⁻¹ were well within the range of measured yields reported in the literature. Measured wheat yields in 24 farmers’ fields in Sirsa district, India, were 0.4 t ha⁻¹ higher than SEBAL estimated wheat yields. Area average WP_ET in the Yaqui Valley was 1.37 kg m⁻³ and could be considered to be high as compared to other irrigated systems around the world where the same methodology was applied. A higher average WP_ET was found in Egypt's Nile Delta (1.52 kg m⁻³), Kings County (CA), USA (1.44 kg m⁻³) and in Oldambt, The Netherlands (1.39 kg m⁻³). The spatial variability of WP_ET within low productivity systems (CV = 0.33) is higher than in high productivity systems (CV = 0.05) because water supply in the former case is uncertain and farming conditions are sub-optimal. The high CV found in areas with low WP_ET indicates that there is considerable scope for improvement. The average scope for improvement in eight systems was 14%, indicating that 14% ET reduction can be achieved while maintaining the same yield. It is concluded that the proposed methodology is accurate and that better knowledge of the spatial variation of WP_ET provides valuable information for achieving local water conservation practices in irrigated wheat.     

Using ESAP software for predicting the spatial distributions of NDVI and transpiration of cotton

Observations of the normalized difference vegetation index (NDVI) from aerial imagery can be used to infer the spatial variability of basal crop coefficients (Kcb), which in turn provide a means to estimate variable crop water use within irrigated fields. However, monitoring spatial Kcb at sufficient temporal resolution using only aerial acquisitions would likely not be cost-effective for growers. In this study, we evaluated a model-based sampling approach, ESAP (EC_e Sampling, Assessment, and Prediction), aimed at reducing the number of seasonal aerial images needed for reliable Kcb monitoring. Aerial imagery of NDVI was acquired over an experimental cotton field having two treatments of irrigation scheduling, three plant density levels, and two N levels. During both 2002 and 2003, ESAP software used input imagery of NDVI on three separate dates to select three ground sampling designs having 6, 12, and 20 sampling locations. On three subsequent dates during both the years, NDVI data obtained at the design locations were then used to predict the spatial distribution of NDVI for the entire field. Regression of predicted versus imagery observed NDVI resulted in r² values from 0.48 to 0.75 over the six dates, where higher r² values occurred for predictions made near full cotton cover than those made at partial cover. Prediction results for NDVI were generally similar for all three sample designs. Cumulative transpiration (Tr) for periods from 14 to 28 days was calculated for treatment plots using Kcb values estimated from NDVI. Estimated cumulative Tr using either observed NDVI from imagery or predicted NDVI from ESAP procedures compared favorably with measured cumulative Tr determined from soil water balance measurements for each treatment plot. Except during late season cotton senescence, errors in estimated cumulative Tr were between 3.0% and 7.3% using observed NDVI, whereas they were they were between 3.4% and 8.8% using ESAP-predicted NDVI with the 12 sample design. Thus, employing a few seasonal aerial acquisitions made in conjunction with NDVI measurements at 20 or less ground locations optimally determined using ESAP, could provide a cost-effective method for reliably estimating the spatial distribution of crop water use, thereby improving cotton irrigation scheduling and management.     

Increasing water productivity of irrigated crops under limited water supply at field scale

Borkhar district is located in an arid to semi-arid region in Iran and regularly faces widespread drought. Given current water scarcity, the limited available water should be used as efficient and productive as possible. To explore on-farm strategies which result in higher economic gains and water productivity (WP), a physically based agrohydrological model, Soil Water Atmosphere Plant (SWAP), was calibrated and validated using intensive measured data at eight selected farmer fields (wheat, fodder maize, sunflower and sugar beet) in the Borkhar district, Iran during the agricultural year 2004-2005. The WP values for the main crops were computed using the SWAP simulated water balance components, i.e. transpiration T, evapotranspiration ET, irrigation I, and the marketable yield Y_M in terms in terms of Y_MT⁻¹, Y_M ET⁻¹ and Y_M I⁻¹.The average WP, expressed as $ T⁻¹ (US $ m⁻³) was 0.19 for wheat, 0.5 for fodder maize, 0.06 for sunflower and 0.38 for sugar beet. This indicated that fodder maize provides the highest economic benefit in the Borkhar irrigation district. Soil evaporation caused the average WP values, expressed as Y_M ET⁻¹ (kg m⁻³), to be significantly lower than the average WP, expressed as Y_MT⁻¹, i.e. about 27% for wheat, 11% for fodder maize, 12% for sunflower and 0.18 for sugar beet. Furthermore, due to percolation from root zone and stored moisture content in the root zone, the average WP values, expressed as Y_MI⁻¹ (kg m⁻³), had a 24-42% reduction as compared with WP, expressed as Y_M ET⁻¹.The results indicated that during the limited water supply period, on-farm strategies like deficit irrigation scheduling and reduction of the cultivated area can result in higher economic gains. Improved irrigation practices in terms of irrigation timing and amount, increased WP in terms of Y_MI⁻¹ (kg m⁻³) by a factor of 1.5 for wheat and maize, 1.3 for sunflower and 1.1 for sugar beet. Under water shortage conditions, reduction of the cultivated area yielded higher water productivity values as compared to deficit irrigation.     

WATPRO: A remote sensing based model for mapping water productivity of wheat

Water productivity in agriculture needs to be improved significantly in the coming decades to secure food supply to a growing world population. To assess on a global scale where water productivity can be improved and what the causes are for not reaching its potential, the current levels must be understood. This paper describes the development and validation of a WATer PROductivity (WATPRO) model for wheat that is based on remote sensing-derived input data sets, and that can be applied at local to global scales. The model is a combination of Monteith's theoretical framework for dry matter production in plants and an energy balance model to assess actual evapotranspiration. It is shown that by combining both approaches, the evaporative fraction and the atmospheric transmissivity, two parameters which are usually difficult to estimate spatially, can be omitted. Water productivity can then be assessed from four spatial variables: broadband surface albedo, the vegetation index NDVI, the extraterrestrial radiation and air temperature. A sensitivity analysis revealed that WATPRO is most sensitive to changes in NDVI and least sensitive to changes in air temperature. The WATPRO model was applied at 39 locations where water productivity was measured under experimental conditions. The correlation between measured and modelled water productivity was low, and this can be mainly attributed to differences in scales and in the experimental and modelling periods. A comparison with measurements from farmer's fields in areas surrounded by other wheat fields located in Sirsa District, NW India, showed an improved correlation. Although not a validation, a comparison with SEBAL-derived water productivity in the same region in India proved that WATPRO can spatially predict water productivity with the same spatial variation.     

Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin

Crop consumptive water use and productivity are key elements to understand basin water management performance. This article presents a simplified approach to map rice (Oryza sativa L.) water consumption, yield, and water productivity (WP) in the Indo-Gangetic Basin (IGB) by combining remotely sensed imagery, national census and meteorological data. The statistical rice cropped area and production data were synthesized to calculate district-level land productivity, which is then further extrapolated to pixel-level values using MODIS NDVI product based on a crop dominance map. The water consumption by actual evapotranspiration is estimated with Simplified Surface Energy Balance (SSEB) model taking meteorological data and MODIS land surface temperature products as inputs. WP maps are then generated by dividing the rice productivity map with the seasonal actual evapotranspiration (ET) map. The average rice yields for Pakistan, India, Nepal and Bangladesh in the basin are 2.60, 2.53, 3.54 and 2.75 tons/ha, respectively. The average rice ET is 416 mm, accounting for only 68.2% of potential ET. The average WP of rice is 0.74 kg/m³. The WP generally varies with the trends of yield variation. A comparative analysis of ET, yield, rainfall and WP maps indicates greater scope for improvement of the downstream areas of the Ganges basin. The method proposed is simple, with satisfactory accuracy, and can be easily applied elsewhere.     

Effects of deficit irrigation on the yield and yield components of drip irrigated cotton in a mediterranean environment

A field study on cotton (Gossypium hirsutum L., cv.) was carried out from 2005 to 2008 in the Çukurova Region, Eastern Mediterranean, Turkey. Treatments were designated as I₁₀₀ full irrigation; DI₇₀, DI₅₀ and DI₀₀ which received 70, 50, and 0% of the irrigation water amount applied in the I₁₀₀ treatment. The irrigation water amount to be applied to the plots was calculated using cumulative pan evaporation that occurred during the irrigation intervals. The effect of water deficit or water stress on crop yield and some plant growth parameters such as yield response, water use efficiencies, dry matter yield (DM), leaf area index (LAI) as well as on lint quality components was evaluated. The average seasonal evapotranspiration ranged from 287 ± 15 (DI₀₀) to 584 ± 80 mm (I₁₀₀). Deficit irrigation significantly affected crop yield and all yield components considered in this study. The average seed cotton yield varied from 1369 ± 197 (DI₀₀) to 3397 ± 508 kg ha⁻¹ (I₁₀₀). The average water use efficiency (WUE_ET) ranged from 6.0 ± 1.6 (I₁₀₀) to 4.8 ± 0.9 kg ha⁻¹ mm⁻¹ (DI₀₀), while average irrigation water use efficiency (WUE_I) was between 9.4 ± 3.0 (I₁₀₀) and 14.4 ± 4.8 kg ha⁻¹ mm⁻¹ (DI₅₀). Deficit irrigation increased the harvest index (HI) values from 0.26 ± 0.054 (I₁₀₀) to 0.32 ± 0.052 kg kg⁻¹ (DI₅₀). Yield response factor (Ky) was determined to be 0.98 based on four-year average. Leaf area index (LAI) and dry matter yields (DM) increased with increasing water use. This study demonstrated that the full irrigated treatment (I₁₀₀) should be used for semiarid conditions with no water shortage. However, DI₇₀ treatment needs to be considered as a viable alternative for the development of reduced irrigation strategies in semiarid regions where irrigation water supplies are limited.     

Crop coefficient, yield response to water stress and water productivity of teff (Eragrostis tef (Zucc.)

In the semi-arid region of Tigray, Northen Ethiopia a two season experiment was conducted to measure evapotranspiration, estimate yield response to water stress and derive the crop coefficient of teff using the single crop coefficient approach with simple, locally made lysimeters and field plots. During the experiment we also estimated the water productivity of teff taking into account long-term rainfall probability scenarios and different levels of farmers’ skills. During the experimental seasons (2008 and 2009), the average potential evapotranspiration of teff ranged from 260 to 317 mm. The total seasonal water requirement of teff was found to lower in contrast to the assumptions of regional agronomists that teff water requirement is comparable to that of wheat and barley (375 mm). The average single crop coefficient values (k_c) for the initial, mid and late season stages of teff were 0.8-1, 0.95-1.1 and 0.4-0.5, respectively. The seasonal yield response to water stress was 1.04, which indicates that teff exhibits a moderately sensitive and linear response to water stress. The results suggest that teff is likely to give significantly higher grain yield when a nearly optimal water supply is provided. The study showed that, in locations where standard equipment is not affordably available, indicative (rough) crop evapotranspiration values can be obtained by using field plots and employing locally made lysimeters. The difference in economic water productivity (EWP) and the crop water productivity (CWP) for teff were assessed under very wet, wet, normal, dry and very dry scenarios. In addition two groups of farmers were evaluated, a moderately (I) and a highly skilled (II) group. The results showed that higher EWP and CWP were obtained under very wet scenario than very dry scenario. There was also a 22% increase in EWP and CWP under group II compared to group I farmers. The increase was due to a 22% reduction in unwanted water losses achieved through use of improved technology and better irrigation skills. Both EWP and CWP can be used to evaluate the pond irrigation water productivity (IWP) for a given climate, crop and soil type, and skill and technology level of the farmer. For special crops like teff extra criteria may be needed in order to properly evaluate the pond irrigation water productivity. During the experimental seasons, a high IWP for teff was attained when about 90% of the optimal water need of the crop was met. IWP can be used as an indicator as how much supplementary irrigation has to be applied in relation to the rainfall and other sources of water supply in order to assure greatest yield from a total area. However, the supplemental irrigation requirement of the crops may vary with season due to seasonal rainfall variability.     

Ground-based remote sensing for assessing water and nitrogen status of broccoli

Remote sensing (RS) can facilitate the management of water and nutrients in irrigated cropping systems. Our objective for this study was to evaluate the ability of several RS indices to discriminate between limited water and limited nitrogen induced stress for broccoli. The Agricultural Irrigation Imaging System (AgIIS) was used over a 1-ha broccoli field in central Arizona to measure green (550 nm), red (670 nm), far red (720 nm), and near infrared (NIR-790 nm) reflectances, and thermal infrared radiation. Measurements were taken at a 1 m × 1 m resolution, every several days during the season. The following indices were calculated: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), normalized difference based on NIR and green reflectance (NDNG), canopy chlorophyll concentration index (CCCI), and the water deficit index (WDI). The experimental design was a two-factor, nitrogen × water, Latin square with four treatments (optimal and low water and optimal and low nitrogen) and four replicates. In addition to RS measurements, the following in-situ measurements were taken: SPAD chlorophyll (closely related to nitrogen status), plant petiole nitrate-nitrogen concentrations, soil water content, and plant height, width, and leaf area index (LAI). Fresh marketable broccoli yield was harvested from plots 130 days after planting.Seasonal water application (irrigation plus rainfall) was 14% greater for optimal than low water treatments, whereas total nitrogen application was 35% greater for optimal than low N treatments. Although both nitrogen and water treatments affected broccoli growth and yield, nitrogen effects were much more pronounced. Compared to the optimal water and nitrogen treatment, broccoli yield was 20% lower for low water but optimal nitrogen, whereas yield was 42% lower for optimal water but low nitrogen. The RVI, NDVI, and NDNG indices detected treatment induced growth retardation but were unable to distinguish between the water and nitrogen effects. The CCCI, which was developed as an index to infer differences in nitrogen status, was found to be highly sensitive to nitrogen, but insensitive to water stress. The WDI provided appropriate information on treatment water status regardless of canopy cover conditions and effectively detected differences in water status following several irrigation events when water was withheld from low but not optimal water treatments. Using a RS ground-based monitoring system to simultaneously measure vegetation, nitrogen, and water stress indices at high spatial and temporal resolution could provide a successful management tool for differentiating between the effects of nitrogen and water stress in broccoli.     

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.     

Evapotranspiration and water use of full and deficit irrigated cotton in the Mediterranean environment in northern Syria

Cotton (Gossypium hirsutum L.) is the most important industrial and summer cash crop in Syria and many other countries in the arid areas but there are concerns about future production levels, given the high water requirements and the decline in water availability. Most farmers in Syria aim to maximize yield per unit of land regardless of the quantity of water applied. Water losses can be reduced and water productivity (yield per unit of water consumed) improved by applying deficit irrigation, but this requires a better understanding of crop response to various levels of water stress. This paper presents results from a 3-year study (2004-2006) conducted in northern Syria to quantify cotton yield response to different levels of water and fertilizer. The experiment included four irrigation levels and three levels of nitrogen (N) fertilizer under drip irrigation. The overall mean cotton (lint plus seed, or lintseed) yield was 2502 kg ha⁻¹, ranging from 1520 kg ha⁻¹ under 40% irrigation to 3460 kg ha⁻¹ under 100% irrigation. Mean water productivity (WP_ET) was 0.36 kg lintseed per m³ of crop actual evapotranspiration (ET_c), ranging from 0.32 kg m⁻³ under 40% irrigation to 0.39 kg m⁻³ under the 100% treatment. Results suggest that deficit irrigation does not improve biological water productivity of drip-irrigated cotton. Water and fertilizer levels (especially the former) have significant effects on yield, crop growth and WP_ET. Water, but not N level, has a highly significant effect on crop ET_c. The study provides production functions relating cotton yield to ET_c as well as soil water content at planting. These functions are useful for irrigation optimization and for forecasting the impact of water rationing and drought on regional water budgets and agricultural economies. The WP_ET values obtained in this study compare well with those reported from the southwestern USA, Argentina and other developed cotton producing regions. Most importantly, these WP_ET values are double the current values in Syria, suggesting that improved irrigation water and system management can improve WP_ET, and thus enhance conservation and sustainability in this water-scarce region.     

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.     

Different indices to characterize water use pattern of micro-sprinkler irrigated onion (Allium cepa L.)

The amount of water used by any crop largely depends on the extent to which the soil water depletion from the root zone is being recharged by appropriate depth of irrigation. To test this hypothesis a field study was carried out in November–March of 2002–2003 and 2003–2004 on a sandy loam (Aeric haplaquept) to quantify the effect of depth of irrigation applied through micro-sprinklers on onion (Allium cepa L.) bulb yield (BY) and water use patterns. Seven irrigation treatments consisted of six amounts of sprinkler applied water relative to compensate crop (K_c) and pan (K_p) coefficient-based predicted evapotranspiration loss from crop field (ET_p) (i) 160% of ET_p (1.6ET_p); (ii) 1.4ET_p; (iii) 1.2ET_p; (iv) 1.0ET_p; (v) 0.8ET_p; (vi) 0.6ET_p; (vii) 40 mm of surface applied water whenever cumulative pan evaporation equals to 33 mm. Water use efficiency (WUE), net evapotranspiration efficiency (WUE_ET) and irrigation water use efficiency (WUE_I) were computed. Marginal water use efficiency (MWUE) and elasticity of water productivity (EWP) of onion were calculated using the relationship between BY and measured actual evapotranspiration (ET_c). Yield increased with increasing sprinkler-applied water from 0.6 to 1.4ET_p. Relative to the yield obtained at 0.6ET_p, yield at 1.0ET_p increased by 23–25% while at 1.4ET_p it was only 3–9% greater than that at 1.0ET_p. In contrast, yield at 1.6ET_p was 9–12% less than that at 1.4ET_p. Maximum WUE (7.21 kg m⁻³) and WUE_ET (13.87 kg m⁻³) were obtained under 1.0ET_p. However, the highest WUE_I (3.83 kg m⁻³) was obtained with 1.2ET_p. The ET_c associated with the highest WUE was 20% less than that required to obtain the highest yields. This study confirmed that critical levels of ET_c needed to obtain maximum BYs, or WUE, could be obtained more precisely from the knowledge of MWUE and EWP.     

Assessing impacts of surge-flow irrigation on water saving and productivity of cotton

To improve water saving and conservation in irrigated agriculture, a range of field evaluation experiments was carried out with various furrow irrigation treatments in cotton fields to estimate the possibilities of improving furrow irrigation performances under conditions of Central Fergana Valley, Uzbekistan. The research consisted in comparing surge and continuous-flow in long furrows and adopting alternate-furrow irrigation. The best results were achieved with surge-flow irrigation applied to alternate furrows. Field data allowed the calibration of a surface irrigation model that was used to identify alternative management issues. Results identified the need to better adjust inflow rates to soil infiltration conditions, cut-off times to the soil water deficits and improving irrigation scheduling. The best irrigation water productivity (0.61 kg m⁻³) was achieved with surge-flow on alternate furrows, which reduced irrigation water use by 44% (390 mm) and led to high application efficiency, near 85%. Results demonstrated the possibility for applying deficit irrigation in this region.     

Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment

The combined use of remote sensing and a distributed hydrological model have demonstrated the improved understanding of the entire water balance in an area where data are scarcely available. Water use and crop water productivity were assessed in the Upper Bhima catchment in southern India using an innovative integration of remotely sensed evapotranspiration and a process-based hydrological model. The remote sensing based Surface Energy Balance Algorithm for Land (SEBAL) was used to derive an 8 month time series of observed actual evapotranspiration from October 2004 to May 2005. This dataset was then used in the calibration of the Soil and Water Assessment Tool (SWAT). This hydrological model was calibrated by changing 34 parameters to minimize the difference between simulated and observed actual evapotranspiration. The calibration efficiency was assessed with four different performance indicators. The calibrated model was used to derive a monthly basin water balance and to assess crop water productivity and crop water use for the irrigation year 2004-2005. It was found that evapotranspiration is the largest water loss in the catchment and total evaporative depletion was 38,172 Mm³ (835 mm). Of the total evaporative depletion 42% can be considered as non-beneficial and could be diverted to other beneficial utilization. Simulated crop water productivities for sugarcane, sorghum and winter wheat are relatively high at 2.9 kg/m³, 1.3 kg/m³ and 1.3 kg/m³, respectively. The frequency distributions of crop water productivity are characterised by low coefficient of variation, yielding limited scope for improvement in the agricultural areas under the current cropping systems. Further improvements in water productivity may however be achieved by shifting the crop base from sugarcane to a dual crop and introducing a fallow period from March to May or by converting non-productive rangelands to bio fuel production or other agricultural land uses.     

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.     

Different indices to characterize water use pattern of irrigated cauliflower (Brassica oleracea L. var. botrytis) in a hot sub-humid climate of India

Frequency and depth of irrigation play crucial role in crop yield and use efficiency of water resource. To test this hypothesis a field study was carried out in November to January of 2001-2002 to 2003-2004 on a sandy loam (Aeric haplaquept) for quantifying the frequency and depth of irrigation on growth, curd yield (CY) and water use pattern of cauliflower (Brassica oleracea L. var. botrytis). Four irrigation frequencies depending on the attainment of cumulative pan evaporation (CPE) values of: 25 (CPE₂₅), 31(CPE₃₁), 38 (CPE₃₈) and 45 (CPE₄₅) mm were placed in main-plots, with three depth of irrigation (IW) of 35 (IW₃₅), 30 (IW₃₀) and 25 (IW₂₅) mm in sub-plots. Water use efficiency (WUE), net evapotranspiration efficiency (WUE_ET) and irrigation water use efficiency (WUE_I) were computed. Marginal water use efficiency (MWUE) and elasticity of water productivity (EWP) were calculated using the relationship between CY and seasonal actual evapotranspiration (SET). A continuous increasing trend in growth parameters, yield and WUE_I was recorded with the increase in SET from CPE₄₅-IW₂₅ to CPE₃₁-IW₃₀. However with further increase in SET the same decreased up to CPE₂₅-IW₃₅ regime. Highest WUE and WUE_ET obtained under CPE₃₈-IW₃₅ regime where SET value was 5% lower than the status of SET under CPE₃₁-IW₃₀. This study confirmed that critical levels of SET needed to obtain maximum curd yield or WUE, could be obtained more precisely from the knowledge of MWUE and EWP.     

Estimation of water consumption and crop water productivity of winter wheat in North China Plain using remote sensing technology

The North China Plain (NCP) is one of the most water stressed areas in the world. The water consumption of winter wheat accounts for more than 50% of the total water consumption in this region. An accurate estimate of the evapotranspiration (ET) and crop water productivity (CWP) at regional scale is therefore key to the practice of water-saving agriculture in NCP. In this research, the ET and CWP of winter wheat in 83 counties during October 2003 to June 2004 in NCP were estimated using the remote sensing data. The daily ET was calculated using SEBAL model with NOAA remote sensing data in 17 non-cloud days whereas the reference daily crop ET was estimated using meteorological data based on Hargreaves approach. The daily ET and the total ET over the entire growing season of winter wheat were obtained using crop coefficient interpolation approach. The calculated average and maximum water consumption of winter wheat in these 83 counties were 424 and 475 mm, respectively. The calculated daily ET from SEBAL model showed good match with the observed data collected in a Lysimeter. The error of ET estimation over the entire growing stage of winter wheat was approximately 4.3%. The highest CWP across this region was 1.67 kg m⁻³, and the lowest was less than 0.5 kg m⁻³. We observed a close linear relationship between CWP and yield. We also observed that the continuing increase of ET leads to a peaking and subsequent decline of CWP, which suggests that the higher water consumption does not necessarily lead to a higher yield.     

Modernization and optimization of irrigation systems to increase water productivity

Population increase and the improvement of living standards brought about by development will result in a sharp increase in food demand during the next decades. Most of this increase will be met by the products of irrigated agriculture. At the same time, the water input per unit irrigated area will have to be reduced in response to water scarcity and environmental concerns. Water productivity is projected to increase through gains in crop yield and reductions in irrigation water. In order to meet these projections, irrigation systems will have to be modernized and optimised. Water productivity can be defined in a number of ways, although it always represents the output of a given activity (in economic terms, if possible) divided by some expression of water input. Five expressions for this indicator were identified, using different approaches to water input. A hydrological analysis of water productivity poses a number of questions on the choice of the water input expression. In fact, when adopting a basin-wide perspective, irrigation return flows often can not be considered as net water losses. A number of irrigation modernization and optimization measures are discussed in the paper. Particular attention was paid to the improvement of irrigation management, which shows much better economic return than the improvement of the irrigation structures. The hydrological effects of these improvements may be deceiving, since they will be accompanied by larger crop evapotranspiration and even increased cropping intensity. As a consequence, less water will be available for alternative uses.