Irrigation Data Research Articles

Jointly Assimilating MODIS LAI and ET Products Into the SWAP Model for Winter Wheat Yield Estimation

Leaf area index (LAI) and evapotranspiration (ET) are two crucial biophysical variables related to crop growth and grain yield. This study presents a crop model-data assimilation framework to assimilate the 1-km moderate resolution imaging spectroradiometer (MODIS) LAI and ET products (MCD15A3 and MOD16A2, respectively) into the soil water atmosphere plant (SWAP) model to assess the potential for estimating winter wheat yield at field and regional scales. Since the 1-km MODIS products generally underestimate LAI or ET values in fragmented agricultural landscapes due to scale effects and intrapixel heterogeneity, we constructed a new cost function by comparing the generalized vector angle between the observed and modeled LAI and ET time series during the growing season. We selected three parameters (irrigation date, irrigation depth, and emergence date) as the reinitialized parameters to be optimized by minimizing the cost function using the shuffled complex evolution method-University of Arizona (SCE-UA) optimization algorithm, and then used the optimized parameters as inputs into the SWAP model for winter wheat yield estimation. We used four data-assimilation schemes to estimate winter wheat yield at field and regional scales. We found that jointly assimilating MODIS LAI and ET data improved accuracy (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.43, RMSE = 619 kg · ha <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) than assimilating MODIS LAI data (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.28, RMSE = 889 kg · ha <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) or ET data (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.36, RMSE = 1561 kg·ha <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) at the county level, which indicates that the proposed estimation method is reliable and applicable at a county scale.

Evaluation of water and nitrogen use efficiencies in a double cropping system under different integrated management practices based on a model approach

Irrigation, fertilization, and cultivation managements play important roles in crop production in the North China Plain (NCP). This study aims to compare crop yields, and water and N use efficiencies (WUE and NUE) in a wheat–maize cropping system under different integrated management practices and recommend the best management practices (BMPs). A two-year experiment involving four integrated management practices was conducted in Tai’an City, Shandong Province in the NCP. These management practices were designed as follows: (1) traditional farming practice (FP); (2) optimized combination of cropping and fertilization (OPT-1); (3) practice for high yield (HY), which does not consider the cost of resource inputs to maximize grain yield; and (4) further optimized combination of cropping and fertilization (OPT-2), which is based on the HY practice. Soil water movement, nitrate transport, and crop growth were all simulated using the soil water, heat, carbon, and N simulation (WHCNS) model. Results indicated that simulated soil water content and nitrate concentration at different depths in soil profiles, leaf area index, dry matter weight, and grain yield were all in good agreement with the field-measured data. Simulation results indicated that the amounts and dates of irrigation and fertilization, planting method, planting density, and sowing date had obvious effects on grain yield, water drainage, total N loss, WUE, and NUE. The annual average total N loss under the OPT-1 practice decreased by about 28.6% compared with the FP practice, whereas the annual average grain yield and NUE increased by 27.7% and 25.7%, respectively. The largest annual average grain yield and total N loss occurred in the HY practice (23,590kgha−1 and 240.6kgNha−1, respectively). Although the annual average grain yield of the OPT-2 practice was 15.4% lower than that of HY practice, the NUE was 19.2% higher in OPT-2 than in HY. The annual average nitrate leaching under the OPT-2 practice was the lowest and reached 25.5%–60.0% compared with those under other practices. Among the four practices, the OPT-2 practice achieved the most preferable results; the lowest N loss and the highest NUE were obtained at the expense of a slight decrease in grain yield. Therefore, the OPT-2 practice was the BMPs among the four practices and should be recommended to maximize the economic and environmental benefits in the study region.

Using Water and Agrochemicals in the Soil, Crop and Vadose Environment (WAVE) Model to Interpret Nitrogen Balance and Soil Water Reserve Under Different Tillage Managements

Abstract Applying models to interpret soil, water and plant relationships under different conditions enable us to study different management scenarios and then to determine the optimum option. The aim of this study was using Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE) model to predict water content, nitrogen balance and its components over a corn crop season under both conventional tillage (CT) and direct seeding into mulch (DSM). In this study a corn crop was cultivated at the Irstea experimental station in Montpellier, France under both CT and DSM. Model input data were weather data, nitrogen content in both the soil and mulch at the beginning of the season, the amounts and the dates of irrigation and nitrogen application. The results show an appropriate agreement between measured and model simulations (nRMSE &lt; 10%). Using model outputs, nitrogen balance and its components were compared with measured data in both systems. The amount of N leaching in validation period were 10 and 8 kgha–1 in CT and DSM plots, respectively; therefore, these results showed better performance of DSM in comparison with CT. Simulated nitrogen leaching from CT and DSM can help us to assess groundwater pollution risk caused by these two systems.

Direct in vivo evidence of immense stem water exploitation in irrigated date palms.

During the summer, evaporative demand at midday often exceeds the transport capacity of most desert plants. However, date palms maintain their ecological dominance with sustained and uniquely high rates of transpiration. This high rate of flow cannot be attributed to soil water supply alone. In order to quantify intra-plant water allocation in irrigated date palms, three water-sensing techniques have been incorporated: heat dissipation, gravimetric sampling, and time domain reflectrometry. Each of these methods has known limitations but their integration resulted in a quantitative in vivo accounting of the date palm diurnal and seasonal water mass balance. By incorporating these methods it was possible to determine that date palms substantially rely on the exploitation and recharge of the stem reservoir in their water budget. The stem of mature date palms can hold up to 1 m(3) of water and supply 25% of daily transpiration (i.e. 5000 l of water in 100 d of summer). The internal stem water reservoir is consistently recharged by over 50 l per night which allows for successive daytime reuse throughout the entire growing season. More broadly, these findings suggest that internal water allocation and night-time soil-water availability could provide useful information for improving date palm irrigation practices.

Three new species of arbuscular mycorrhizal fungi discovered at one location in a desert of Oman: Diversispora omaniana, Septoglomus nakheelum and Rhizophagus arabicus

Three new species of arbuscular mycorrhizal (AM) fungi (Glomeromycota) were isolated from soil samples collected from a hyperarid sandy plain of South Arabia. Morphological characteristics of the spores clearly differentiated them from closely related AM species. Molecular analyses were performed on rDNA sequences obtained from single spores including a ~1700 bp region comprising partial SSU, ITS, partial LSU and the ~600 bp ITS region only. The phylogenetic trees based on these regions showed that the three species belong to well described genera but are clearly distinct from known species. Consequently, we describe them here as Diversispora omaniana, Septoglomus nakheelum and Rhizophagus arabicus spp. nov. D. omaniana and R. arabicus were isolated from the native, arid habitat, while S. nakheelum was isolated from a nearby irrigated date palm plantation. The discovery of three new species of AM fungi from this location suggests that a number of additional undescribed AM taxa may be present in such desert ecosystems. Further work to understand the diversity and functional significance of these new AM taxa may offer new opportunities for conservation, re-vegetation, and sustainable agriculture in extremely arid environments.

Impacts of Climate Change on Agricultural Production in Enugu State,Nigeria

Climate Change is increasingly one of the most serious national security threats which will have significant impacts on natural resources, ecosystem and biodiversity. At the same time, it is likely to trigger food insecurity, human migration, economic, and social depression, environmental and political crisis, thereby affecting national development. To analyze the climate change impact on agricultural productivity in Enugu state, the study used primary data that have been collected from Enugu State Agricultural Development Programme (ENADP) on productivity for four decades. Also, rainfall data for thirty years (1981–2010) were collected from Nigeria Meteorological Agency to generate seasonality index and reliability index. The data have been analyzed using descriptive statistics and correlation analysis. Also, literatures were identified for review through a comprehensive search by using electronic and non-electronic databases. Related published literature and documents were searched in a systematic way using a range of key words relating to climate change impacts and agriculture. The study showed a general change in the seasonal rainfall regime. Rainfall regime in the state falls under a markedly seasonal regime with a long drier season; and a reliability of rainfall regime characterized by a more marked variability in the months of maximum rainfall. These changes are notable indicators of climate change. Again, the study showed that all the traditional crops with the exception of cassava and pepper had a significant field decrease as rainfall continued to be more erratic. The literature review indicates that climate change and agriculture both have double-barrel effect on each other. Reducing climate change – induced threats to agriculture that contributes to national development, there will be a need for farmers in Enugu to respond by planting different climate– adapted species, using pesticides and altering the dates of planting, harvesting and irrigation.

Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion

Continuous monitoring of daily evapotranspiration (ET) at field scale can be achieved by combining thermal infrared remote sensing data information from multiple satellite platforms, given that no single sensor currently exists today with the required spatiotemporal resolution. Here, an integrated approach to field-scale ET mapping is described, combining multi-scale surface energy balance evaluations and a data fusion methodology, namely the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), to optimally exploit spatiotemporal characteristics of image datasets collected by the Landsat and Moderate resolution Imaging Spectroradiometer (MODIS) sensors, as well as geostationary platforms. Performance of this methodology is evaluated over adjacent irrigated and rainfed fields, since mixed conditions are the most challenging for data fusion procedures, and in two different climatic regions: a semi-arid site in Bushland, TX and a temperate site in Mead, NE. Daytime-total ET estimates obtained for the Landsat overpass dates suggest that the intrinsic model accuracy is consistent across the different test sites (and on the order of 0.5mmd−1) when contemporaneous Landsat imagery at 30-m resolution is available. Comparisons between tower observations and daily ET datastreams, reconstructed between overpasses by fusing Landsat and MODIS estimates, provide a means for assessing the strengths and limitations of the fused product. At the Mead site, the model performed similarly for both irrigated and rainfed fields, with an accuracy of about 0.9mmd−1. This similarity in performance is likely due to the relatively large size of the fields (≈50ha), suggesting that the soil moisture dynamics of the irrigated fields are reasonably well captured at the 1-km MODIS thermal pixel scale. On the other hand, the accuracy of daily retrievals for irrigated fields at the Bushland site was lower than that for the rainfed field (errors of 1.5 and 1.0mmd−1, respectively), likely due to the inability of the model to capture ET spikes right after irrigation events for fields substantially smaller than MODIS data resolution. At this site, the irrigated fields were small (≈5ha) compared to the MODIS pixel size, and sparsely distributed over the landscape, so sporadic contributions to ET from soil evaporation due to irrigation were not captured by the 1-km MODIS ET retrievals. However, due the semiarid environment at Bushland, these irrigation-induced spikes in soil evaporation are not long-lived and these underestimations generally affect the irrigation dates only and they do not seem to influence negatively the estimates at the seasonal scale. ET data fusion is expected to perform better over agricultural areas where irrigation is more spatially continuous, resulting in moisture fluxes that are more uniform at the MODIS pixel scale. Overall, the model accurately reproduces the ET temporal dynamics for all the experimental sites, and is able to capture the main differences that were observed between irrigated and rainfed fields at both daily and seasonal time scales.

Irrigation scheduling based on CERES-Wheat model for spring wheat production in the Minqin Oasis in Northwest China

The Minqin County in Northwest China is known for its serious desertification and irrigation-dependent oasis farming that is mainly distributed along the Shiyang River. To answer some important hypothetical questions related to optimal irrigation scheduling for spring wheat (Triticum aestivum L.) production in the Minqin Oasis, the CERES-Wheat model in DSSAT V4.5 was used to simulate the spring wheat growth in irrigated farmland in this area. The results of model simulation indicate that if the soil water content is lower than 65% of field capacity (or about 190mm water) in the 1-m depth soil profile during the grain filling and milk ripe stages, the final grain yield can be remarkably reduced (e.g. more than 1000kgha−1 for some treatments in field experiment) even for a short period of water stress. The water stress in the early stages could be eliminated with luxurious water supply, but more nitrogen would be washed away from the soil profile and then the yield was impacted. The optimized irrigation dates played an important role in improving the water use efficiency of spring wheat. If there was only a single irrigation allowed by the limited water resources, the irrigation date should be at the end of booting or beginning of heading stage. If the second irrigation could be adjusted to the middle of heading stage, the 3-irrigation schedule (a total of three irrigations in the whole growth season, and so forth) could meet the water demand of spring wheat without losing too much yield (e.g. less than 20kgha−1 when compared with the 4-irrigation treatment). Furthermore, if the first irrigation of the 4-irrigation schedule could be delayed to the starting of jointing, the simulated yield could be increased from about 6500kgha−1 to the highest 7000kgha−1. Finally, the analysis of uncertainties of simulated dry yields across 58 years historical weather data showed that the schedules with fewer irrigation events cause larger uncertainties due to local weather variations. The 4-irrigation schedule seemed to be the best choice for spring wheat at the Minqin Oasis due to its relatively higher long-term average yields and lower uncertainties since it was under non-limited water conditions.

MODFLOW Modeling to Solve Drainage Problems in the Argaman Date Palm Orchard, Jordan Valley, Israel

Overwetting and soil salinization processes are common in irrigated date palm orchards in Israel. Subsurface drainage systems are generally used to overcome soil salinity. Subsurface drainage models can contribute to the selection of a proper drainage system and its proper placement in the field. In this paper, the groundwater flow modeling program MODFLOW was used to simulate groundwater levels in a date palm orchard in Argaman, in the Jordan Valley, Israel. Using a three-layer groundwater flow model, the most efficient drainage system was a combination of 4.5-m depth primary drains and 3-m depth drains of different lengths installed at a different spacing between drains. Installation of this drainage system would cost approximately NIS$2.6 million, i.e., 30% less than the initially proposed project. Given certain input, a spatially distributed groundwater flow model such as MODFLOW can provide more reliable information than different analytical solutions for planning an effective subsurface drainage system.

Effect of Dry Matter Accumulation Characteristics on Yield of Winter Wheat Analyzed by Dynamic Simulation Model

To disclose the quantitative relationship between yield and dry matter accumulation in winter wheat, we designed three field experiments to obtain wheat populations with varying sowing date, basic seedlings, amounts of basic fertilizers, date and quantity of topdressed nitrogen fertilizer, irrigation amounts before wintering, amounts and date of irrigation after regreening of wheat in 2009–2010 and 2010–2011 growing seasons. Dry matter accumulation before wintering was represented by dry weight per plant and total stem and tiller numbers at prewintering stage, while dry matter after wintering was described by the Logistic curve characteristics based on relative accumulated temperature (R GDDi ). The grain yield and yield components of winter wheat were closely related to characteristic parameters such as maximum rate of dry matter accumulation and two inflection points in the curve for dry matter accumulation rate. Paired-sample t-test was used to validate the models established, and no significant difference was observed between the simulated and observed values. The results indicate that the Logistic model is able to describe the process of dry matter accumulation and the formation of grain yield and its components in winter wheat. The models established can be used in analysis of population regulation in winter wheat.

Development of Variable Threshold Models for detection of irrigated paddy rice fields and irrigation timing in heterogeneous land cover

Accurate monitoring of irrigated paddy field area and irrigation timing are of a great concern in agricultural water management due to the substantial consumption of fresh water when irrigating paddy fields. Spectral threshold methods (Xiao et al., 2005) have been widely applied to detect irrigated paddy fields and irrigation timing using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI). These methods applied constant additive threshold values (T) to LSWI and compared it to EVI to detect the irrigated paddy fields. In this study, we developed Variable Threshold Models that utilized different pixel-based threshold values depending on sub-pixel land cover heterogeneity and hence, improve detection performance on distributed small-scale paddy fields. Non-irrigated sub-pixels were quantified with irrigation maps produced by Synthetic Aperture Radar (SAR) microwave images. Significant positive correlation between EVI and the sub-pixel numbers of non-irrigated area were found (r=0.87), which resulted in higher T for MODIS pixels with more non-irrigated sub-pixels. Accordingly, a Variable Threshold Model, i.e. a regression model between T and EVI, was developed. With the Variable Threshold Model, agreement rates between MODIS and SAR-based irrigated small-scale paddy field classification doubled compared with that from a fixed threshold value. In comparison with field observations, the Variable Threshold Models showed a mean error of +0.9 days, an improvement over the mean error of +2.8 days from a fixed threshold model. Combined utilization of SAR and MODIS images provides a useful tool for developing a Variable Threshold Model that can enhance accurate monitoring of irrigation dates across heterogeneous paddy field regions.

ESTIMATION OF THE PAPAYA CROP COEFFICIENTS FOR IMPROVING IRRIGATION WATER MANAGEMENT IN SOUTH OF HAVANA

The papaya (Carica papaya L.) is a main irrigated fruit crop in Cuba and in the tropical and subtropical regions. For environmental and irrigation management purposes, it is important to accurately estimate its crop evapotranspiration and irrigation requirements. The objective of the present study is to determine the crop coefficients (Kc) and the depletion fraction for no stress (p) of the papaya, variety Maradol, as cultivated in southern Havana. Experiments took place during the period March - November, 1997 in an experimental area where soils are compacted red iron soils. The ISAREG irrigation simulation model was applied to those observed data. The calibration of the model consisted in searching the crop coefficients and the depletion fraction for no stress that minimize the differences between observed and simulated available soil water. Several statistical indicators were used to assess the goodness of fit. Results show a good adjustment between observations and model predictions, with the regression coefficient forced to the origin close to 1 (b = 1.01) and a high R2 = 0.86. The root mean square error (RMSE) and the average absolute error (AAE) are small, respectively RMSE = 6.5 mm and AAE = 4.9 mm. After calibration, the model was used to assess the current irrigation scheduling; results show that irrigation dates were anticipated relative to the required and irrigation depths were excessive, thus significant percolation occurred. The ISAREG model will be further used to generate and evaluate alternative irrigation schedules aimed at improved water productivity.

English

In order to study the effect of planting dates and different irrigation regimes on yield and yield components of six canola cultivars, an experiment was conducted in two growing seasons; 2008 to 2009 and 2009 to 2010. Six canola cultivars (Zarfam, GKH1103, GKH1605, GKH2005, GKH305 and GKH3705) were cultivated in two different dates (October 7th and November 6th) with two levels of irrigation regimes (irrigation after 60 mm evaporation from Class A evaporation pan and irrigation interrupting at flowering stage). The experiments were conducted in randomized complete block design arrangement in split factorial with four replications The results demonstrated that late planting date and interrupting of irrigation at flowering stage significantly decreased growth, yield and yield components the of canola cultivars. In addition, oil yield was affected by late planting and water stress and it was dramatically decreased. Also, there was no significant difference among the cultivars with respect to oil percentage. The highest seed yield (5930.4 kg. ha -1 ) was obtained from GKH1103 cultivars planted on October 7th under the conditions of full irrigation. Seed yield and oil yield in the second year was more than that of the first year; this increase was related to the increase in seed weight and pod number per plant but not to number of seed per pod. In general, canola cultivation on November 6th considerably decreased seed and oil yield and it is an important point to achieve desirable yield to seed sowing not done later than October 7th. Additionally, complementary irrigation was very important to gain high yield in canola under the conditions of this study. Key words: Canola, planting date, water stress, yield and yield components.

Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region

Abstract. The aim of this study is to propose methods to improve crop and water management in Mediterranean regions. At landscape scale, there is a spatial variability of agricultural practices, particularly for grasslands irrigated by flooding. These grasslands are harvested three times per year and produce high quality hay, but their productions decreased significantly during the last few years because of the water scarcity. It is therefore important to assess the real water requirement for crops in order to predict productions in the case of agricultural practice modifications. Until now, the spatial variability of agricultural practices was obtained through surveys from farmers, but this method was tedious to describe an entire region. Thus, the specific aim of the study is to develop and assess a new method based on a crop model for estimating water balance and crop yield constrained by products derived from optical remote sensing data with high spatio-temporal resolution. A methodology, based on the combined use of FORMOSAT-2 images and the STICS crop model, was developed to estimate production, evapotranspiration and drainage of irrigated grasslands in "the Crau" region in the South Eastern France. Numerous surveys and ground measurements were performed during an experiment conducted in 2006. Simple algorithms were developed to retrieve the dynamic of Leaf Area Index (LAI) for each plot and the main agricultural practices such as mowing and irrigation dates. These variables computed from remote sensing were then used to parameterize STICS, applied at region scale to estimate the spatial variability of water budget associated with the biomass productions. Results are displayed at the farm scale. Satisfactory results were obtained when compared to ground measurements. The method for the extrapolation to other regions or crops is discussed as regard to data available.

EFFECTS OF PLANTING DATE AND IRRIGATION DATE ON QUALITATIVE AND QUANTITATIVE CHARACTERISTICS OF CUMIN (CUMINUM CYMINUM L.)

Cumin is one of the most important drug plants that has many uses in food and drug technology. In order to investigate its drought resistance and determine the best date of planting, this experiment has been conducted in the form of split plot RCB design with 3 replications. Treatments were date of planting (main plot) at 4 levels (25 th Nov. D1, 27 th Dec. D2, 19 th Feb. D3 and 19 th Mar. D4) and date of irrigation (sub plot) at 4 levels (complete irrigation 11, twice irrigation (seed germination and stem elongation) I2, twice irrigation (seed germination and flowering) I3 and twice irrigation (seed germination and seed formation) I4) in 2007-2008. Traits under study were percent of essential oil, 1000 seed weight, no. of umbels per plant, seed no. per umbels, lateral shoots, final height, biological yield, seed yield and harvest index. Date of planting had significant effect on essential oil percent, 1000 seeds weight, no of seed per umbels, no of umbels per plant and final height at 1 % level. Also, irrigation date had significant effect on no. umbels per plant, no. of lateral shoots, biological yield and seed yield at 5% level. Interaction of planting date and irrigation date were significant for no. of lateral shoots, biological yield, seed yield and biomass at 5% level. Mean comparison had been done by Duncan's test that showed there were significant differences among means of traits at different planting date treatments, except harvest index at 5% level. Also, there were significant differences among means of traits at different date of irrigation treatments for essence percent, 1000 seeds weight, no. of umbels per plant, final height and harvest index. Also, there were significant differences among interaction of date of planting and date of irrigation for all traits at 5% level. The highest essential oil percent was related to D2I2 treatment equal to 1.8%. Also, the highest seed yield and biological yield occurred at D2I1 treatment. Then the best treatment was 27 th December planting date with complete irrigation.

Technical Note: Scheduling for Deficit Irrigation—Crop Yield Predictor

Irrigators in many countries with dwindling water supplies face the prospect that they will not be able to fully irrigate their crops. In these cases, they still need to schedule their water applications to make the best economic use of available water. Major scheduling questions for deficit irrigation include: (1) will pre-season irrigation be beneficial; and (2) when should irrigation be started and stopped during the growing season. Traditional irrigation scheduling estimates crop evapotranspiration (ETc) to predict the amount and timing of irrigation events for the next several days. Usually these schedules assume that the water supply will provide irrigation to fully irrigate the crop to produce maximum crop yields. Irrigators practicing deficit irrigation need to predict irrigation schedules in advance of the growing season and make appropriate adjustments based on potential crop yields and economic returns. A computerized decision tool, the Crop Yield Predictor (CYP), has been developed to forecast yields from alternative irrigation schedules and designed for management decisions by irrigators, crop consultants, and extension personnel. Users of CYP determine soil water status before or during the cropping season and formulate potential schedules of irrigation dates and amounts. Soil water holding capacity and irrigation system water delivery capacity are constraints on the ability to supply water to the crop. CYP uses a daily soil water balance coupled with computations of effective evapotranspiration (ETe) to predict crop yields from regional yield-ET relationships. Multiple executions of CYP with alternative irrigation schedules lead to the schedules that project optimum net economic returns from the management scenarios. CYP is an example of adapting a crop simulation model into a tool for those who need to make irrigation management decisions.

Irrigation and soil physical quality: An investigation at a long‐term irrigation site

The hypothesis that irrigation improves soil quality by improving its moisture holding capacity compared to dryland (non‐irrigated) soils was tested using data on soil physical properties and irrigation frequency and timing (dryland, and irrigated at 10, 15, and 20% v/v and 3‐weekly) from a long‐term irrigation trial at Winchmore, South Island, New Zealand (soil type: Lismore silt loam). Despite previous work showing that macroporosity decreases and bulk density increases with irrigation and grazing, the most frequently irrigated plots showed no significant difference in these measurements, or in saturated and unsaturated hydraulic conductivity, compared to dryland plots. This implies that the soil had an inherent resilience to soil physical degradation. With time (years), the number of irrigations had declined and date of the first irrigation needed during the irrigation season had become later, leading to the perception of improved moisture holding capacity. This was supported by an increase in soil carbon concentrations in all treatments with time since development. Irrigations were scheduled, on average, at 10.9, 15.3 and 20.6% v/v for 10, 15, and 20% treatments, respectively, until 1997, but at 9.9, 14.1 and 19.2% for 10, 15, and 20% treatments, respectively, afterwards. However, several reasons explain this and refute the hypothesis of improved moisture holding capacity. The most pertinent was that irrigation timing was probably affected by the use of a gravimetric method prior to 1997, and a TDR‐based technique since. In addition, no difference was seen in pasture production relative to irrigation with time. Thus, apart from soil C concentrations there was little conclusive evidence to support the hypothesis that irrigation improves soil moisture holding capacity at this site.

EFFECT OF NITROGEN FERTILIZATION AND LAST IRRIGATION ON YIELD AND QUALITY OF SUGAR BEET (Beta vulgaris L.) IN NORTHERN DELTA

Two field experiments were carried out at the Experimental Farm of EL-Serw Agricultural Station, Dommiata Governorate ,Agricultural Research Center ,Egypt during the two successive seasons of 2006/07 and 2007/08.The aim of this investigation to study the effect of nitrogen levels at rates of (80,100 and 120 kg N/fed) and three withholding irrigation dates of the last irrigation (3,4 and 5 weeks before harvest) on yield and quality of sugar beet . The results showed that: 1- There is significant effect of nitrogen fertilizer levels on root diameter, root fresh weight , purity %, root and sugar yields (t/fed) in both seasons and significant for sucrose percentage in the second season, TSS% in the first season while it is insignificant effect for root length in both seasons. The treatment of 120kgN/fed increased root yield by 64.157 % and 25.78% and sugar yield by 53.23% 21.25% compared by addition 80 kg N/fed in both seasons. 2- Effect of withholding last irrigation was significant for root length ,sucrose percentage ,sugar yields in both seasons and significant effect on root fresh weight in the second season and root yield in the first season and insignificant effect on purity percentage in both seasons. Applying the irrigation 5 weeks before harvest gave the lowest root length ,root fresh weight and the lowest root and sugar yields while gave the highest sucrose and purity percentages in both seasons. 3- The interaction between nitrogen fertilizer levels and withholding of last irrigation was significant effect on root length and root fresh weight in the second season ,TSS% in the first season and sucrose percentage in both seasons ,but it was insignificant effect on root diameter, root and sugar yields in both seasons. 4- From this study we can advise to use nitrogen fertilization at rate of 120 kg/fed and date of last irrigation 4 weeks before harvest to obtain the maximum yield and quality of sugar beet in East Northern Delta.

Irrigation and Planting Date Effects on Seed Yield and Agronomic Traits of Early-Maturing Soybean

ABSTRACT Soybean [Glycine max (L.) Merr.] growers in the mid-south United States have increasingly practiced early planting and double-cropping systems. Information on crop management is desired by soybean growers to improve production and profitability. Effects of irrigation and planting date on seed yield and other agronomic traits were investigated in soybean cultivars from eight maturity groups (MG) in 2002 and 2003 at two locations in Arkansas. The planting date (April, May, and June) and irrigation treatments significantly affected seed yield, plant height, and maturity. Significant effects were also observed for number of nodes, number of pods, and number of seeds per plant, whereas number of branches per plant was not affected by planting date and irrigation treatments. Irrigation improved seed yield by an average of 83% (986 kg/ha) in all experiments conducted across two years. Highest seed yield was achieved when soybeans were planted in May, followed by April and then by June planting. The MG V and VI cultivars, conventionally grown in Arkansas, produced higher seed yields than other maturity groups and were the most suitable cultivar selections when considering seed yield alone. Significant interactions were observed among planting date, irrigation, and maturity groups/genotypes. The MG IV was a better candidate for the double-cropping system (June-planting) because of its earlier maturity and high seed yield. For the early soybean production system (April-planting), MG I and II cultivars were potentially good selections because of their short growing periods and acceptable seed yields. The various planting dates and irrigation systems combined with proper cultivar selections provide soybean producers with more options for using the land and water efficiently.

Irrigation scheduling for furrow-irrigated maize under climate uncertainties in the Thrace plain, Bulgaria

Climate change creates uncertainties for irrigation management. To cope with them, simulations were performed for the present and scenario-built weather conditions that include a pessimistic scenario of precipitation decrease in the next 25 years. In a former study, the irrigation scheduling simulation model ISAREG was calibrated for two maize varieties: the water stress-resistant hybrid Kn-2L-611 and the water stress-sensitive hybrid H708. Both are subjects of this study, which compares four irrigation scheduling alternatives: (1) refilling the soil reservoir and adopting a management-allowed depletion fraction (MAD) of 0.47; (2) refilling the soil reservoir and adopting MAD=0.33; (3) partially refilling the soil reservoir and adopting MAD=0.47; and (4) crop without irrigation. For the very dry year and the present climate all alternative irrigation schedules behave similarly but for the average year, alternatives 1 and 3, allowing a larger soil water depletion with MAD=0.47, require less water than the alternative with MAD=0.33. However, analysis of impact on yields using simulations relative to every year during 1970–1992 shows that alternative 2 leads to less impact on yields. The results of simulations were compared with irrigation schedules presently advised in the region and show that the latter do not fully cover crop requirements in dry seasons, when some yield decrease occurs. Simulations for the pessimistic scenario show that all three irrigation scheduling alternatives can easily accommodate the foreseen changes mainly by selecting suitable irrigation dates. The results of simulations do not allow selecting one among the three alternatives as the best irrigation scheduling strategy but are useful for later building an information system for farmers using actual weather data. Relative to the rainfed crop, the results indicate that yield impacts highly increase for the pessimistic scenario, particularly for the water stress-sensitive hybrid H708. The results indicate that vulnerability to climate change is higher for non-irrigated crops and that coping with possible rainfall decreases requires adopting less sensitive crop varieties, including when deficit irrigation would be applied for water saving.