Irrigated agriculture: Water resources management for a sustainable environment

In the last decade, research on irrigation has mainly been aimed at reducing crop water consumption. In arid and semi-arid environments, in relation to the limited water resources, the use of low quality water in agriculture has also been investigated in order to detect their effects on soil physical properties and on crop production. More recently, even the reduction of energy consumption in agriculture, as well as the effects of external factors, climate change and agricultural policies, have been major research interests. All these objectives have been considered in the papers included in this special issue. However, in the last years, approaches aimed at reducing crop water requirements have significantly changed. Remote sensing with satellites or unmanned vehicles, and vegetation spectral measurements, among others, represent in fact the newest frontier of existing technologies. Knowledge of soil hydraulic properties, often forgotten because of the difficulty of their estimation, can also be considered as a new way to reduce water consumption.

Water use efficiency and water productivity in the Spanish irrigation district ¿Río Adaja?

A study of the assessment of the irrigation water use has been carried out in the Spanish irrigation District “Río Adaja” that has analyzed the water use efficiency and the water productivity indicators for the main crops for three years: 2010-2011, 2011-2012 and 2012-2013. A soil water balance model was applied taking into ccount climatic data for the nearby weather station and soil properties. Crop water requirements were calculated by the FAO Penman- Monteith with the application of the dual crop coefficient and by considering the readily vailable soil water content (RAW) concept. Likewise, productivity was measured by the indexes: annual relative irrigation supply (ARIS), annual relative water supply (ARWS), relative rainfall supply (RRS), the water productivity (WP), the evapotranspiration water productivity (ETWP), and the irrigation water productivity (IWP. The results show that in most crops deficit irrigation was applied (ARIS<1) in the first two years however, the IWP improved. This was higher in 2010-2011 which corresponded to the highest effective precipitation Pe. In general, the IWP (€.m-3) varied amongcrops but crops such as: onion (4.14, 1.98 and 2.77 respectively for the three years), potato (2.79, 1.69 and 1.62 respectively for the three years), carrot (1.37, 1.70 and 1.80 respectively for the three years) and barley (1.21, 1.16 and 0.68 respectively for the three years) showed the higher values. Thus, it is highlighted the y could be included into the cropping pattern which would maximize the famer’s gross income in the irrigation district.

Sugarcane water use from shallow water tables: implications for improving irrigation water use efficiency

The resource potential of shallow water tables for cropping systems has been investigated using the Australian sugar industry as a case study. Literature concerning shallow water table contributions to sugarcane crops has been summarised, and an assessment of required irrigation for water tables to depths of 2 m investigated using the SWIMv2.1 soil water balance model for three different soils. The study was undertaken because water availability is a major limitation for sugarcane and other crop production systems in Australia and knowledge on how best to incorporate upflow from water tables in irrigation scheduling is limited. Our results showed that for the three soils studied (representing a range of permeabilities as defined by near-saturated hydraulic conductivities), no irrigation would be required for static water tables within 1 m of the soil surface. Irrigation requirements when static water tables exceeded 1 m depth were dependent on the soil type and rooting characteristics (root depth and density). Our results also show that the near-saturated hydraulic conductivities are a better indicator of the ability of water tables below 1 m to supply sufficient upflow as opposed to soil textural classifications. We conclude that there is potential for reductions in irrigation and hence improvements in irrigation water use efficiency in areas where shallow water tables are a low salinity risk: either fresh, or the local hydrology results in net recharge. (C) 2003 Elsevier B.V. All rights reserved.

Jujube fruit water relations during fruit maturation stage under different water deficit conditions

The fruit maturation stage is considered the optimal phenological stage for implementing water deficitin jujube (Zizyphus jujuba Mill.), since a low, moderate or severe water deficit at this time has no effect onyield, fruit volume or eating quality. However, no information exists at fruit water relations level on themechanisms developed by Z. jujuba to confront drought. The purpose of the present study was to increaseour understanding of the relationship between leaf and fruit water relations of jujube plants under dif-ferent irrigation conditions during fruit maturation, paying special attention to analysing whether fruitsize depends on fruit turgor. For this, adult jujube trees (cv. Grande de Albatera) were subjected to fiveirrigation treatments. Control plants (T0) were irrigated daily above their crop water requirements inorder to attain non-limiting soil water conditions in 2012 and 2013. T1 plants were subjected to deficitirrigation throughout the 2012 season, according to the criteria frequently used by the growers in thearea. T2 (2012), T3 and T4 (2013) were irrigated as T0 except during fruit maturation, in which irrigationwas withheld for 32, 17 and 24 days, respectively. The results indicated that the jujube fruit maturationperiod was clearly sensitive to water deficit. During most of this stage water could enter the fruits viathe phloem rather than via the xylem. From the beginning of water withholding to when maximumwater stress levels were achieved, fruit and leaf turgor were maintained in plants under water deficit.However, a direct relation between turgor and fruit size was not found in jujube fruits, which could bedue to an enhancement of a cell elasticity mechanism (elastic adjustment) which maintains fruit turgorby reducing fruit cells size or to the fact that jujube fruit growth depends on the fruit growth-effectiveturgor rather than just turgor pressure.

Climate change and irrigation water requirement at Jaguaribe river basin, semi-arid northeast of Brazil.

Summary: Climate change has a potential to impact rainfall, temperature and air humidity, which have relation to plant evapotranspiration and crop water requirement. The purpose of this research is to assess climate change impacts on irrigation water demand, based on future scenarios derived from the PRECIS (Providing Regional Climates for Impacts Studies), using boundary conditions of the HadCM3 submitted to a dynamic downscaling nested to the Hadley Centre regional circulation model HadRM3P. Monthly time series for average temperature and rainfall were generated for 1961-90 (baseline) and the future (2040). The reference evapotranspiration was estimated using monthly average temperature. Projected climate change impact on irrigation water demand demonstrated to be a result of evapotranspiration and rainfall trend. Impacts were mapped over the target region by using geostatistical methods. An increase of the average crop water needs was estimated to be 18.7% and 22.2% higher for 2040 A2 and B2 scenarios, respectively. Objective ? To analyze the climate change impacts on irrigation water requirements, using downscaling techniques of a climate change model, at the river basin scale. Method: The study area was delimited between 4º39?30? and 5º40?00? South and 37º35?30? and 38º27?00? West. The crop pattern in the target area was characterized, regarding type of irrigated crops, respective areas and cropping schedules, as well as the area and type of irrigation systems adopted. The PRECIS (Providing Regional Climates for Impacts Studies) system (Jones et al., 2004) was used for generating climate predictions for the target area, using the boundary conditions of the Hadley Centre model HadCM3 (Johns et al., 2003). The considered time scale of interest for climate change impacts evaluation was the year of 2040, representing the period of 2025 to 2055. The output data from the climate model was interpolated, considering latitude/longitude, by applying ordinary kriging tools available at a Geographic Information System, in order to produce thematic maps.

Seasonal dynamics and operational monitoring of hedgerow olive tree transpiration in response to applied water

We used 2012 sap flow measurements to assess the seasonal dynamics of daily plant transpiration (ETc) in a high-density olive orchard (Olea europaea L. cv. ‘Arbequina’) with a well-watered (HI) control treatment A to supply 100 % of the crop water needs, and a moderately (MI) watered treatment B that replaced 70% of crop needs. To assure that treatment A was well-watered, we compared field daily ETc values against ETc obtained with the Penman-Monteith (PM) combination equation incorporating the Orgaz et al. (2007) bulk daily canopy conductance (gc) model, validated for our non-limiting conditions. We then tested the hypothesis of indirectly monitoring olive ETc from readily available vegetation index (VI) and ground-based plant water stress indicator. In the process we used the FAO56 dual crop coefficient (Kc) approach. For the HI olive trees we defined Kcb as the basal transpiration coefficient, and we related Kcb to remotely sensed Soil Adjusted Vegetation Index (SAVI) through a Kcb-SAVI functional relationship. For the MI treatment, we defined the actual transpiration ETc as the product of Kcb and the stress reduction coefficient Ks obtained as the ratio of actual to crop ETc, and we correlated Ks with MI midday stem water potential (ψst) values through a Ks-ψ functional relationship. Operational monitoring of ETc was then implemented with the ETc = Kcb(SAVI)Ks(ψ)ETo relationship stemmed from the FAO56 approach and validated taking as inputs collected SAVI and ψst data reporting to year 2011. Low validation error (6%) and high goodness-of-fit of prediction were observed (R2 = 0.94, RSME = 0.2 mm day-1, P = 0.0015), allowing to consider that under field conditions it is possible to predict ETc values for our hedgerow olive orchards if SAVI and water potential (ψst) values are known.

Assessing the sustainability of wheat-based cropping systems using APSIM: Model parameterisation and evaluation

Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998-99 and 1999-2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM's cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat-fallow and wheat-chickpea rotations (1987-98) were nevertheless well simulated when the soil water content in 0-0.45 m soil depth was set to 'air dry' at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH 4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM's nitrogen module. APSIM was capable of predicting long-term trends (1985-98) in soil organic matter in wheat-fallow and wheat-chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the sustainability of wheat-chickpea rotations at Tel Hadya.

Zero tillage and nitrogen fertiliser application in wheat and barley on a Vertosol in a marginal cropping area of south-west Queensland

Winter cereal cropping is marginal in south-west Queensland because of low and variable rainfall and declining soil fertility. Increasing the soil water storage and the efficiency of water and nitrogen (N) use is essential for sustainable cereal production. The effect of zero tillage and N fertiliser application on these factors was evaluated in wheat and barley from 1996 to 2001 on a grey Vertosol. Annual rainfall was above average in 1996, 1997, 1998 and 1999 and below average in 2000 and 2001. Due to drought, no crop was grown in the 2000 winter cropping season. Zero tillage improved fallow soil water storage by a mean value of 20 mm over 4 years, compared with conventional tillage. However, mean grain yield and gross margin of wheat were similar under conventional and zero tillage. Wheat grain yield and/or grain protein increased with N fertiliser application in all years, resulting in an increase in mean gross margin over 5 years from $86/ha, with no N fertiliser applied, to $250/ha, with N applied to target ≥13% grain protein. A similar increase in gross margin occurred in barley where N fertiliser was applied to target malting grade. The highest N fertiliser application rate in wheat resulted in a residual benefit to soil N supply for the following crop. This study has shown that profitable responses to N fertiliser addition in wheat and barley can be obtained on long-term cultivated Vertosols in south-west Queensland when soil water reserves at sowing are at least 60% of plant available water capacity, or rainfall during the growing season is above average. An integrative benchmark for improved N fertiliser management appears to be the gross margin/water use of ~$1/ha.mm. Greater fallow soil water storage or crop water use efficiency under zero tillage has the potential to improve winter cereal production in drier growing seasons than experienced during the period of this study.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

Drought stress characterization of post-rainy season (rabi) sorghum in India

During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

Identifying the Function of Sorghum's Drought Tolerance Stay-Green QTL

The goal of this research is to understand the function of allelic variation of genes underpinning the stay-green drought adaptation trait in sorghum in order to enhance yield in water-limited environments. Stay-green, a delayed leaf senescence phenotype in sorghum, is primarily an emergent consequence of the improved balance between the supply and demand of water. Positional and functional fine-mapping of candidate genes associated with stay-green in sorghum is the focus of an international research partnership between Australian (UQ/DAFFQ) and US (Texas A&M University) scientists. Stay-green was initially mapped to four chromosomal regions (Stg1, Stg2, Stg3, and Stg4) by a number of research groups in the US and Australia. Physiological dissection of near-isolines containing single introgressions of Stg QTL (Stg1-4) indicate that these QTL reduce water demand before flowering by constricting the size of the canopy, thereby increasing water availability during grain filling and, ultimately, grain yield. Stg and root angle QTL are also co-located and, together with crop water use data, suggest the role of roots in the stay-green phenomenon. Candidate genes have been identified in Stg1-4, including genes from the PIN family of auxin efflux carriers in Stg1 and Stg2, with 10 of 11 PIN genes in sorghum co-locating with Stg QTL. Modified gene expression in some of these PIN candidates in the stay-green compared with the senescent types has been found in preliminary RNA expression profiling studies. Further proof-of-function studies are underway, including comparative genomics, SNP analysis to assess diversity at candidate genes, reverse genetics and transformation.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

无压灌溉日光温室番茄作物-皿系数研究

以-25 kPa作为土壤水势临界值,将作物—皿系数(Kcp)设为0.2,0.4,0.6,0.8,1.0,1.2六个处理,研究了不同灌溉水量时的番茄产量、品质和灌溉水利用效率。通过经济效益评价,研究了杨凌地区无压灌溉温室番茄获得最高经济效益时的作物—皿系数。通过张力计读数变化规律,研究了利用张力计测量无压灌溉湿润体内土壤水势的特点。研究结果表明,Kcp为0.2~0.8时,灌溉水量的增加对番茄产量影响不大;Kcp为1.0~1.2时,灌溉水量的增加能显著提高番茄产量和果实大小;Kcp为0.2时的灌溉水量能极显著提高番茄的灌溉水利用效率。在综合考虑了杨凌地区水价、番茄使用目的和市场价格波动规律后,Kcp取值1.2能获得最高的经济效益。作物—皿系数法计算灌溉水量时的滞后性特点和张力计埋设位置,是判断利用张力计监测土壤水势临界值方法有效性的两个重要因素。