Simulation of furrow irrigation practices (SOFIP): a field-scale modelling of water management and crop yield for furrow irrigation

Because of the spatial and temporal variabilities of the advance infiltration process, furrow irrigation investigations should not be limited to a single furrow irrigation event when using a modelling approach. The paper deals with the development and application of simulation of furrow irrigation practices (SOFIP), a model used to analyse furrow irrigation practices that take into account spatial and temporal variabilities of the advance infiltration process. SOFIP can be used to compare alternative furrow irrigation management strategies and find options that mitigate local deep-percolation risks while ensuring a crop yield level that is acceptable to the farmer. The model is comprised of three distinct modelling elements. The first element is RAIEOPT, a hydraulic model that predicts the advance infiltration process. Infiltration prediction in RAIEOPT depends on a soil moisture deficit parameter. PILOTE, a crop model, which is designed to simulate soil water balance and predict yield values, updates the soil moisture parameter. This parameter is an input of a parameter generator (PG), the third model component, which in turn provides RAIEOPT with the data required to simulate irrigation at the scale of an N-furrow set. The study of sources of variability and their impact on irrigation advance, based on field observations, allowed us to build a robust PG. Model applications show that irrigation practices must account for inter-furrow advance variability when optimising furrow irrigation systems. The impact of advance variability on deep percolation and crop yield losses depends on both climatic conditions and irrigation practices.     

Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture

We present an innovative approach to explore water management options in irrigated agriculture considering the constraints of water availability and the heterogeneity of irrigation system properties. The method is two-folds: (i) system characterization using a stochastic data assimilation procedure where the irrigation system properties and operational management practices are estimated using remote sensing (RS) data; and (ii) water management optimization where we explored water management options under various levels of water availability. We set up a soil–water–atmosphere–plant model (SWAP) in a deterministic–stochastic mode for regional modeling. The distributed data, e.g. sowing dates, irrigation practices, soil properties, depth to groundwater and water quality, required as inputs for the regional modeling were estimated by minimizing the residuals between the distributions of field-scale evapotranspiration (ET) simulated by the regional application of SWAP, and by surface energy balance algorithm for land (SEBAL) using two Landsat7 ETM+ images. The derived distributed data were used as inputs in exploring water management options. Genetic algorithm was used in data assimilation and water management optimizations. The case study was conducted in Bata minor (lateral canal), Kaithal, Haryana, India during 2000–2001 rabi (dry) season. Our results showed that under limited water condition, regional wheat yield could improve further if water and crop management practices are considered simultaneously and not independently. Adjusting sowing dates and their distribution in the irrigated area could improve the regional yield, which also complements the practice of deficit irrigation when water availability is largely a constraint. This result was also found in agreement with the scenario that water is non-limited with the exception that the farmers have more degrees of freedom in their agricultural activities. An improvement of the regional yield to 8.5% is expected under the current scenario.     

Field-scale assessment of deep drainage risk

Improving irrigation efficiency is of primary importance in arid and semi-arid regions of the world as a consequence of increasing incidences of soil and water salinisation. In the cotton-growing regions of Australia salinisation is generally a result of inefficient irrigation practices, which lead to excessive deep drainage (DD). There is therefore the need to apply a relatively inexpensive approach to assessing where inefficiencies occur and make prediction of suitability of existing and new water storage sites. However, physical methods of measuring DD, such as flux meters and lysimeters, are time-consuming and site-specific. In this paper we apply a rapid method for determining the spatial distribution of soil in an irrigated cotton field in the lower Gwydir valley. First, EC_a data (using EM38 and EM31) were used to determine a soil-sampling scheme for determining soil information such as clay content and exchangeable cations to a depth of 1.2 m. The soil data and water quality information were input into the SaLF (salt and leaching fraction) model to estimate DD rate (mm/year). In developing the relationship between EC_a and estimated DD, three exponential models (two-, three- and four-parameter) were compared and evaluated using the Aikakie information criteria (AIC). The three-parameter exponential model was found to be best and was used for further analysis. Using the geostatistical approach of multiple indicator kriging (MIK), maps of conditional probability of DD exceeding a critical cut-off value (i.e. 50, 75, 100 mm) were produced for various rates of irrigation (I=300, 600, 1,200 and 1,500 mm/year). The areas of highest risk were consistent with where water-use efficiency was problematic and thus leading to the creation of perched water tables. The advantage of this approach is that it is quick and is applicable to situations where efficient use of water is required. The results can be used for irrigation planning, particularly in the location of large irrigation infrastructure such as water reservoirs.     

Estimating actual irrigation application by remotely sensed evapotranspiration observations

Water managers and policy makers need accurate estimates of real (actual) irrigation applications for effective monitoring of irrigation and efficient irrigation management. However, this information is not readily available at field level for larger irrigation areas. An innovative inverse modeling approach was tested for a field in an irrigation scheme in southern Spain where observed actual evapotranspiration by satellites was used to assess irrigation application amounts. The actual evapotranspiration was used as the basis for an optimization procedure using the physical based SWAP model and the parameter optimization tool PEST. To evaluate the proposed techniques two steps were taken. First, actual observed evapotranspiration from remote sensing was used to optimize two parameters of the SWAP model to determine irrigation applications. Second, a forward-backward approach was applied to test the minimum overpass return time of satellites and the required accuracy of remotely sensed actual evapotranspiration for accurate assessment of irrigation applications. Results indicate that irrigation application amounts can be estimated reasonably accurately, providing data are available at an interval of 15 days or shorter and the accuracy of the signal is 90% or higher.     

Comparison of numerical, analytical, and empirical models to estimate wetting patterns for surface and subsurface drip irrigation

Due to increasing competition for water resources by urban, industrial, and agricultural users, the proportion of agricultural water use is gradually decreasing. To maintain or increase agricultural production, new irrigation systems, such as surface or subsurface drip irrigation systems, will need to provide higher water use efficiency than those traditionally used. Several models have been developed to predict the dimensions of wetting patterns, which are important to design optimal drip irrigation system, using variables such as the emitter discharge, the volume of applied water, and the soil hydraulic properties. In this work, we evaluated the accuracy of several approaches used to estimate wetting zone dimensions by comparing their predictions with field and laboratory data, including the numerical HYDRUS-2D model, the analytical WetUp software, and selected empirical models. The soil hydraulic parameters for the HYDRUS-2D simulations were estimated using either Rosetta for the laboratory experiments and inverse analysis for the field experiments. The mean absolute error (MAE) was used to compare the model predictions and observations of wetting zone dimensions. MAE for different experiments and directions varied from 0.87 to 10.43 cm for HYDRUS-2D, from 1 to 58.1 cm for WetUp, and from 1.34 to 12.24 cm for other empirical models.     

Modeling the effects of saline water use in wheat-cultivated lands using the UNSATCHEM model

Waters of poor quality are often used to irrigate crops in arid and semiarid regions, including the Fars Province of southwest Iran. The UNSATCHEM model was first calibrated and validated using field data that were collected to evaluate the use of saline water for the wheat crop. The calibrated and validated model was then employed to study different aspects of the salinization process and the impact of rainfall. The effects of irrigation water quality on the salinization process were evaluated using model simulations, in which irrigation waters of different salinity were used. The salinization process under different practices of conjunctive water use was also studied using simulations. Different practices were evaluated and ranked on the basis of temporal changes in root-zone salinity, which were compared with respect to the sensitivity of wheat to salinity. This ranking was then verified using published field studies evaluating wheat yield data for different practices of conjunctive water use. Next, the effects of the water application rate on the soil salt balance were studied using the UNSATCHEM simulations. The salt balance was affected by the quantity of applied irrigation water and precipitation/dissolution reactions. The results suggested that the less irrigation water is used, the more salts (calcite and gypsum) precipitate from the soil solution. Finally, the model was used to evaluate how the electrical conductivity of irrigation water affects the wheat production while taking into account annual rainfall and its distribution throughout the year. The maximum salinity of the irrigation water supply, which can be safely used in the long term (33 years) without impairing the wheat production, was determined to be 6 dS m^?1. Rainfall distribution also plays a major role in determining seasonal soil salinity of the root zone. Winter-concentrated rainfall is more effective in reducing salinity than a similar amount of rainfall distributed throughout autumn, winter, and spring seasons.     

Best management of pesticide — furrow irrigation systems

Summary Effects of furrow irrigation designs, water management practices (irrigation scheduling, etc.), soil types and pesticide parameters on pesticide leaching were simulated. A hydraulic kinematic-wave irrigation model was used to estimate water infiltration for alternative furrow lengths and inflow rates. A one-dimensional simulation model then simulated the movement of pesticides through soils following furrow irrigation. Potential ground-water contamination by pesticides can be reduced by an integrated use of the best management practices (BMPs) such as careful selection and use of pesticides, efficient furrow irrigation designs and improved water management techniques (irrigation scheduling, etc.). Procedures for designing an appropriate furrow irrigation system for a particular site and pesticide, and selecting pesticides for a particular site, crop and furrow irrigation system are illustrated. These procedures are being used to develop decision support computer models for developing different BMPs for pesticide-agricultural management decisions.     

SPFC: a tool to improve water management and hay production in the Crau region

This article deals with the development and application of SPFC, a model used to improve water and grassland production (HC) in this region of France. This model is composed of two sub-models: an irrigation model and a crop model. As the fields are border-irrigated, these two sub-models are coupled. The crop model simulates dry matter (DM), leaf area index (LAI) and soil water reserve (SWR) variations. LAI and SWR are both used for border model updating: SWR for the deficit of saturation required by the infiltration equation and LAI for the roughness coefficient n. After calibration and validation, SPFC is then used to identify realistic management strategies for the irrigation and production system at the plot level. By scheduling irrigation when SWR is 50% depleted, would result in a low Dry Matter DM production loss (around 10%), reduced labour (eight irrigation events instead of 11) and in significant water saving compared with farmers’ practices, on the basis of an average climatic scenario. Furthermore, this improvement of irrigation efficiency is not incompatible with groundwater recharge used for the potable water supply of the region.     

Determination of spatial water requirements at county and regional levels using crop models and GIS: An example for the State of Parana,Brazil

Due to the competitive use of available water resources, it has become important to define appropriate strategies for planning and management of irrigated farmland. To achieve effective planning, accurate information is needed for crop water use requirements, irrigation withdrawals, runoff and nitrate leaching as a function of crop, soil type and weather conditions at a regional level. Interfacing crop models with a geographic information system (GIS) extends the capabilities of the crop models to a regional level. The objective of this study was to determine the irrigation requirements, annual runoff and annual nitrate leaching for the most important crops of the Tibagi river basin in the State of Parana, Brazil. The computer tool selected for this study was the Decision Support System for Agrotechnology Transfer (DSSAT) version 3.5 (98.0) and its associated crop modeling and spatial application system AEGIS/WIN. It was assumed that farms within the same county use similar management practices. To achieve representative estimates of irrigation requirements, the weather data from stations located within each county or the nearest weather station were used. A weighting factor based on the proportion of soil type and crop acreage was applied to determine total annual irrigation withdrawals, annual runoff and nitrate leaching for each county in the river basin. The model predicted outputs, including yield, irrigation requirements, runoff and nitrate leached for different soil types in each county, were analyzed, using spatial analysis methods. This allowed for the display of thematic maps for irrigation requirements, annual runoff and nitrate leaching, and to relate this information with irrigation management and planning. The maximum annual irrigation withdrawal, runoff and nitrate leaching were 22,969 m³ per year, 31,152 m³ per year and 1488 t N per year in the Tibagi river basin. This study showed that crop simulation models linked to GIS can be an effective planning tool to help determine irrigation requirements for river basins and large watersheds.     

Evaluation of crop yield models for cowpea in Nigeria

Three phasic models namely, Hanks (H-2), Stewart (S-2) and the Hall–Butcher (H–B), were evaluated on cowpea irrigated using a line source sprinkler system. Three sets of field data (1983, 1985, and 1986) were collected; the 1985 data were used for calibration while the 1983 and 1986 data were used for evaluation of the models. The model performance that most accurately matched the measured data was then used to simulate the most water-efficient irrigation schedule and deficit irrigation analysis for cowpea in Nigeria. Results showed that the models gave good estimates of cowpea grain yield with the H-2 model performing slightly better than the other two models. The weighted root mean square deviations were 0.043, 0.094, and 0.213 for the H-2, S-2 and the H–B model, respectively. Simulation studies with the H-2 model showed that irrigating at 40% moisture depletion is the most water-efficient schedule for cowpea and that greater yield from a given optimum seasonal water application for deficit irrigation can be achieved by splitting the seasonal deficit among the growth stages.     

Water flow and salt transport in cracking clay soils of the Imperial Valley, California

The principles of irrigation and drainage in cracking soils differ markedly from non-cracking soils, and are not thoroughly understood. This paper presents a conceptual model to simulate water and salt flows in cracking soils of the Imperial Valley, CA, in the presence of ground water that contributes partially to ET demand of crops. A salt reactivity function is introduced in the model to account for mineral precipitation (salt deposition) and mineral dissolution (salt pick up). The conceptual water flow model assumes that surface irrigation water moves into the cracks, infiltrates horizontally to wet the soil profile and a fraction bypasses below the root zone into the shallow ground water and is retained for later crop extraction via upflow. Then, water drains vertically through the soil profile step by step, and root water extractions are calculated. When ET exceeds available water upflow of ground water is calculated. Provision for reclamation leaching before the next crop is also made. The associated conceptual salt transport model involves complete mixing of invading and resident soil water. Salt concentration from ET is subjected to a salt reactivity function to obtain salt deposition of calcite and gypsum to obtain salt concentration after precipitation. This reactivity function is also used in the inverse when two or more waters mix to transform salt after precipitation to salt concentration after ET. The flow of salts follows the water transport algorithum. The model has been applied to a point in the Imperial Valley and observed data from Bali et al. (2001) was used for calibration. Simulated point data from four successive years of alfalfa, reclamation leaching, wheat and lettuce are evaluated in this paper.     

On-farm performance evaluation of improved traditional small-scale irrigation practices: A case study from Dire Dawa area, Ethiopia

Field evaluation of surface irrigation systems play a fundamental role to determine the efficiency of the system as it is being used and to identify management practices and system configurations that can be implemented to improve the irrigation efficiency. This study evaluated the performance of an ‘improved’ traditional small-scale irrigation practice at Adada, a representative small-scale irrigation practice in Dire Dawa Administrative Council, Eastern Ethiopia. In order to determine numerical values of performance measures, certain parameters were measured/observed before, during and after an irrigation event while farmers are performing their normal irrigation practice. These parameters include: irrigated crop, irrigation method, stream size, cutoff time, soil moisture deficiency, and field size, shape and spacing. The results showed that the irrigation water applied to a farmer's plot during an irrigation event/turn was generally higher than the required depth to be applied per event. Since the irrigation method used was end-dyked, the major cause of water loss was due to deep percolation. The deep percolation loss was 32% in sorghum, 57% in maize, and 70% in tomato and potato fields. The type of irrigation system used, the ridged irrigation practice and the poor irrigation scheduling in the study sites were the main problems identified in the management and operations of the schemes. The following corrective measures are recommended to improve the system: (1) farmers should regulate the depth of irrigation water they apply according to the type of crop and its growth stage, change the field irrigation system and/or configuration especially for shallow rooted row crops, to furrow system, (2) guidance and support to farmers in developing and introduction of appropriate irrigation scheduling, and (3) future development interventions towards improvement of traditional irrigation practices should also focus in improving the on farm irrigation systems in addition to improving physical infrastructure of the scheme.     

Using EPIC model to manage irrigated cotton and maize

Simulation models are becoming of interest as a decision support system for management and assessment of crop water use and of crop production. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of cotton and maize under South Texas conditions. Simulation of the model was performed to determine crop yield, crop water use, and the relationships between the yield and crop water use parameters such as crop evapotranspiration (ETc) and water use efficiency (WUE). We measured actual ETc using a weighing lysimeter and crop yields by field sampling, and then calibrated the model. The measured variables were compared with simulated variables using EPIC. Simulated ETc agreed with the lysimeter, in general, but some simulated ETc were biased compared with measured ETc. EPIC also simulated the variability in crop yields at different irrigation regimes. Furthermore, EPIC was used to simulate yield responses at various irrigation regimes with farm fields’ data. Maize required ∼700 mm of water input and ∼650 mm of ETc to achieve a maximum yield of 8.5 Mg ha⁻¹ while cotton required between 700 and 900 mm of water input and between 650 and 750 mm of ETc to achieve a maximum yield of 2.0-2.5 Mg ha⁻¹. The simulation results demonstrate that the EPIC model can be used as a decision support tool for the crops under full and deficit irrigation conditions in South Texas. EPIC appears to be effective in making long-term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for in-season irrigation management.     

A real-time water allocation model for large irrigation systems

In this study a simulation model for real-time irrigation scheduling of water deliveries at the tertiary and secondary canal levels of large irrigation systems has been developed. The model is responsive to current season changes in weather and other variables. The irrigation scheduling of the subsequent week is found out at the end of each week by updating the status of the system with real time data up to that week and then by solving the model for the new conditions. The model is based on water balance approach for lowland paddy and a soil moisture simulation approach for determining the irrigation requirements of upland crops. Expected rainfall at different probability levels during the irrigation season was used based on past rain fall data and Leaky law. The model was applied to an irrigation system in Thailand for determining the required irrigation deliveries. Result of the application indicate that the model can be used for determining water deliveries in a real-time basis.     

Performance assessment of Doroodzan irrigation network by steady state hydraulic modeling

There is a need for improvement in the operation and management of many irrigation and drainage systems worldwide. Computer models are used widely for better management. One of such models is HEC-RAS that was applied to Ordibehesht Canal at the Doroodzan irrigation network, northwest of Fars province in the southern Iran. The model was calibrated and validated for two irrigation seasons during 2001 and 2002. The present gate opening rules used to control the offtakes were simulated by the model and the discharge reductions were evaluated. Discharge reduction of offtakes due to discharge reductions at system source were evaluated by the model. Results show that the present rule is not appropriate for the present system. Fluctuations of discharge at the beginning of canal show considerable and nonuniform changes in discharge of offtakes along the Ordibehesht Canal. The head offtakes show more reductions in the water delivered than middle and tail offtakes. A new sensitivity indicator was defined and used to show the response of offtakes due to discharge changes at system source. The study also shows that HEC-RAS model can be used successfully for a large and complex irrigation system for evaluation of its performance in the absence of observed flow data and improvement of irrigation management plans.     

Application of a simulation based optimization model for winter wheat irrigation scheduling in North China

Irrigation needs to be scheduled properly for winter wheat, the main food crop in North China where the water resources are limited. We optimized the irrigation timing of crops under limited water supply by integrating a soil water balance model, dated water production function with cumulative function of water sensitivity index, and a nonlinear search method. The optimization produced the optimal irrigation date series with the predetermined irrigation quota for each application, which aims to obtain higher crop yield with limited irrigation water and be convenient for irrigation management. This simulation–optimization model was used to investigate the irrigation scheduling of winter wheat in Xiaohe irrigation Area in North China. Results show that optimal irrigation date series, corresponding relative yield and relative evapotranspiration are all closely related to the irrigation quota and initial soil water conditions. For rich and medium initial soil water conditions in medium precipitation year, it takes four times of irrigation (60 mm each time) after greening in order to obtain higher crop yield. But it increases to five times for poor initial condition. With limited irrigation water, irrigation should generally be applied in the preferential sequence of early May or late April (in the jointing stage), then mid and late May (in the heading stage), and finally March (in the greening stage). Irrigation should be applied earlier with lower initial soil water storage. Higher irrigation quota increases the crop yield but tends to decrease the marginal value, especially when irrigation quota exceeds 180 mm. The study also indicates that the optimized relative yield is generally higher than that obtained in field experiment. Based on the optimization, we proposed to use the quadratic polynomial function to describe the frontier water production function, which shows the mathematical relationship between optimized relative yield and relative evapotranspiration.     

A simple visual aid for sugarcane irrigation scheduling

Irrigation scheduling based on soil water balance is a simple procedure that can be operated either manually or using computer programs. Adoption of the procedure is still low due to lack of soil water parameters and availability of climatic information. Furthermore, potential users are deterred by both the time and paper work required to carry out the calculations. In this study a visual device in the form of a plastic container was designed and tested to schedule sugarcane (Saccharum spp.) irrigation. The calibrated plastic bucket was field tested and proved to be an effective way to program sugarcane irrigation. It works simultaneously as a pluviometer and as an evaporimeter and, once it is marked, there is no need for human intervention beyond checking the position of the water level in relation to the irrigation control marks. It could be used with other crops and is useful for regions where meteorological data is scarce or difficult to obtain.     

基于神经网络算法的果树需水预测研究

【目的】准确预测果树需水量。【方法】对采集地果园环境数据进行主成分分析,筛选出影响果树蒸腾量的关键因子。建立以长短时记忆(LSTM)神经网络为基础的预测模型来预测果树蒸腾量。为提高预测的精度,在LSTM神经网络的基础上加入了注意力(Attention)机制,形成Attention-LSTM预测模型。【结果】将改进的模型与其他模型的预测精度进行对比,仿真试验表明,该模型的预测精度最高,RMSE和MSE分别为0.487和0.062。【结论】该预测模型可以准确预测果树蒸腾量,从而实现果园精准灌溉并提高水果产量,具有一定的实际意义。     

Assessing basin irrigation and scheduling strategies for saving irrigation water and controlling salinity in the upper Yellow River Basin, China

Water saving in irrigation is a key concern in the Yellow River basin. Excessive water diversions for irrigation waste water and produce waterlogging problems during the crop season and soil salinization in low lands. Supply control and inadequate functionality of the drainage system were identified as main factors for poor water management at farm level. Their improvement condition the adoption of water saving and salinity control practices. Focusing on the farm scale, studies to assess the potential for water savings included: (a) field evaluation of current basin irrigation practices and further use of the simulation models SRFR and SIRMOD to generate alternative improvements for the surface irrigation systems and (b) the use of the ISAREG model to simulate the present and improved irrigation scheduling alternatives taking into consideration salinity control. Models were used interactively to define alternatives for the irrigation systems and scheduling that would minimize percolation and produce water savings. Foreseen improvements refer to basin inflow discharges, land leveling and irrigation scheduling that could result in water savings of 33% relative to actual demand. These improvements would also reduce percolation and maintain water table depths below 1 m thereby reducing soil salinization.     

Adaptation of water and nitrogen management of spring barley and potato as a response to possible climate change in Ireland

Changes in water and nitrogen management for spring barley and potato, arising from possible climate change in Ireland, were assessed using simulation models. The locations in Ireland with the highest proportion (by area) of barley and potato production were identified and 1961–1990 and 2041–2070 monthly climate data were used to drive mechanistic crop models. Nitrogen and water response curves were created using current recommended management guidelines as a starting point. A series of step-wise manual irrigation simulations were then undertaken to estimate the minimum future irrigation demand for specific areas. It was concluded that there will be little impact on spring barley production, but in some areas (towards the centre and western half of Ireland) it might be possible to reduce nitrogen application rates by half. The impact of climate change on potato production will be more pronounced: without irrigation yield will only remain viable in areas where rainfall remains high, elsewhere between 150 and 300 mm of irrigation will be required each year, but this might be offset by the possibility of reducing nitrogen inputs by up to half. It was also concluded that potato production on less suitable (heavier) soils would be less desirable if irrigation is required because of possible run-off losses that may occur.