Farmers’ scheduling patterns in on-demand pressurized irrigation

Abstract

Irrigation scheduling results from the irrigator's integration of meteorological, environmental and crop information. In this paper, the irrigation scheduling patterns of a group of irrigators in the Candasnos Water Users Association (WUA), located in north-eastern Spain, were analysed. Scheduling sprinkler and drip irrigation in this WUA shows additional complications due to the sharing of a collective pressurized irrigation network and to the need to file water orders two days in advance of its foreseen use. The database created by a remote surveillance and control system was mined to obtain the time evolution of hydrant operation time during the 2004–2008 irrigation seasons. Records were selected for clearly identified crops and irrigation systems, and for verified water allocations. Hydrant operation showed a relationship with meteorology (precipitation, wind speed, relative humidity and air temperature), although this relationship was often not evident when hydrants were individually analysed. Statistical analyses were run to classify irrigator's scheduling practices, leading to the establishment of ten different groups. The adopted classification criteria included the average number of weekly irrigations, the SD of the number of weekly irrigations and the modal range of the irrigation starting time. The irrigation pattern was determined by the irrigator (56%), the irrigation system (33%), and the crop (11%). Only in a fraction of the cases (22%) the time change in the scheduling pattern responded to a clear time trend; in 39% of the cases, changes in time appeared random. Further, 45% of the irrigators used the same irrigation pattern in at least half of their hydrant-years, independently of the crop. Only 14% of the irrigators applied different irrigation scheduling patterns to different crops. Our results suggest that irrigators do not find value or do not have the capacity to develop irrigation patterns more consistent and adapted to the local environment, the crops and the irrigation systems.

Introduction

On-farm irrigation scheduling is an important topic of study at two different levels. At the farm level, irrigation scheduling will determine crop yield in both quantity and quality. At the collective level, the addition of the irrigation flows demanded at the hydrants of an irrigation network (resulting from farmer's irrigation scheduling), will determine the network demand and operating conditions throughout the irrigation season.

Designing an on-farm irrigation schedule in a pressurized irrigation system implies selecting the timing, duration and frequency of the irrigation events (Clemmens, 1987). The search for maximum uniformity and efficiency in each irrigation event is an additional constrain to irrigation scheduling. On-farm irrigation system design determines maximum irrigation uniformity and application efficiency. Reaching maximum performance in each irrigation event will depend on the adequate selection of irrigation time and duration. These variables are selected at the beginning of the irrigation event, although irrigation duration can be modified at any time. In the case of sprinkler irrigation, the environmental conditions (subjected to relevant inter- and intra-day variability) will strongly determine irrigation uniformity and wind drift and evaporation losses. Selecting the most adequate irrigation time and duration will minimize the negative effect of environmental conditions on the performance of each irrigation event (Playán et al., 2005) and will maximize irrigation efficiency and/or crop yield. In pressurized irrigation systems requiring electrical energy input, irrigation timing may result in different costs. For instance, in the current conditions in Spain, energy costs can be tripled during a 24 h period.

Collective pressurized irrigation networks are designed to meet certain simultaneity, characterized by the number of open hydrants in each network segment (Lamaddalena and Sagardoy, 2000). During network operation, the time evolution of the number of open hydrants is determined by the physical design of the on-farm irrigation systems, crop water requirements, energy costs and the Water Users Association (WUA) organizational rules. However, the approach of individual farmers to on-farm irrigation scheduling strongly determines hydrant operation, and can provide valuable information for the optimization of irrigation network design and maintenance.

In collective pressurized irrigation networks, design decisions often pose relevant constraints to farmer irrigation scheduling. Relevant limitations derive from the installation of flow limiting valves at the hydrants. Flow limits determine the maximum number of sprinklers or drippers in simultaneous operation or the pivot size. Flow limits also determine the maximum crop water requirements that can be met by the irrigation system. This may result in continuous irrigation operation during the period of peak crop water requirements, regardless of the intraday and interday changes in environmental conditions or energy costs. Regarding the WUAs’ organizational rules, rigid schedules deriving from the planning of pumping stations or energy use can result in severe limitations to farmers’ capacity to respond to crop water requirements.

On-farm irrigation controllers have been designed to implement farmers’ scheduling decisions. However, on-farm controllers have often been reported to complicate the implementation of optimum, environment-sensitive irrigation scheduling (Zapata et al., 2009). Users should master their advanced irrigation controllers in order to implement all features leading to scheduling flexibility. Most of the agricultural irrigation controllers in the market have very limited possibilities in this respect, and have been designed to produce rigid irrigation schedules.

If the characteristics of the collective pressurized irrigation network, the on-farm irrigation system and the controller are important for an adequate irrigation schedule, the human factor stands as the most decisive factor. It is the farmer who judges the available information and produces the schedule leading to the execution of an irrigation event. The farmer may also decide to interrupt irrigation when agrometeorological conditions are not suitable for the irrigation system. In order to make these decisions, a farmer can count on several information sources. Web pages have been created to publish current irrigation requirements for the most common crops in a given region (Department of Water Resources, 2011, Government of Aragón, 2011). Additionally, continuous education programs are available to farmers, particularly to those established in large irrigation projects. As a consequence, most professional farmers are aware of the effect of agrometeorological conditions on irrigation scheduling (regarding crop water requirements and the effect on sprinkler irrigation performance). This is particularly important in areas characterized by strong winds, since wind speed is the agrometeorological factor most limiting to sprinkler irrigation performance (Tarjuelo et al., 1999, Zapata et al., 2007, Sanchez et al., 2010). In drip irrigation, farmers’ scheduling decisions are not so directly influenced by the environment, and often respond to fertigation requirements or to regulated deficit irrigation strategies (Zapata et al., submitted for publication a, Zapata et al., submitted for publication b).

Researchers have paid attention to the effect of farmers’ decision making on several aspects of agricultural production. The most common target of these research works is the influence of human factors on decision making about cropping patterns. Research works have focused on issues such as water scarcity (Faysse, 2003), wastewater irrigation (Styczen et al., 2010), or fluctuations in the price of agricultural commodities (Cortignani and Severini, 2009). The effect of the human factor on irrigation decision making has received limited attention in the literature. Clemmens and Dedrick (1992) analysed a list of candidate factors (including human factors) affecting farm water use in the surface-irrigated area of Maricopa (AZ, USA). Dechmi et al. (2003) used the same methodology to assess the effect of farmer related variables on seasonal irrigation depth and crop yield. Merot et al. (2008) studied the relationship between irrigation practices and crop management in a surface-irrigated area specializing in hay production. Finally, Brown et al. (2010) developed tools to predict the influence of farmers’ irrigation decisions on the final crop yield.

The analysis of detailed on-farm pressurized irrigation schedules has not been the target of recent research efforts. Scientific works have often been oriented to simulating and/or recommending irrigation schedules (Cancela et al., 2006, Liyuan et al., 2010). Other studies have focused on monitoring on-farm irrigation, proposing optimum irrigation calendars (Chopart et al., 2007). However, detailed studies of farmer irrigation scheduling can be used to elucidate current trends in on-farm pressurized irrigation. Researchers can use such studies as a source for insight and to validate irrigation decision making models. On the other hand, irrigation engineers can use these analyses as to improve network and on-farm designs. As a consequence, assessing the factors guiding farmers’ irrigation scheduling will lead to more water- and cost-effective future pressurized collective irrigation networks.

Remote surveillance and control systems (RSCSs) are being installed in many irrigation networks in Spain built in this century. These systems can provide valuable information on individual farmers’ irrigation schedules. As a consequence, RSCS can not only provide a service to the farmers but also provide feedback to irrigation practitioners and analysts. This process is often limited by the database structure (not oriented to data analysis) and by the enormous amount of information often produced by these systems. These findings underline the fact that RSCSs are rarely designed taking into consideration the long-term feedback value of the information they store. As a consequence, data mining techniques are required to produce useful information for the analysis of farmers’ irrigation scheduling. Data mining concerns the extraction of useful information from large amounts of data (Han and Kamber, 2006). In order to obtain knowledge from large databases the first step is data cleaning, followed by data integration if different sources of information are used. Once all information sources are located in the same platform, data selection and transformation will be required if only part of these data is useful or if data presentation is not adequate. Data mining will be followed by pattern evaluation and knowledge presentation.

In this work, the RSCS of an on-demand pressurized WUA located in north-eastern Spain was analysed. The research objectives were to: (1) build a database on hydrant irrigation (30 min interval) for sprinkler and drip irrigation combining crop, year, hydrant, farmer, agrometeorology and irrigation system; (2) classify the irrigation seasons recorded at the WUA hydrants according to their irrigation scheduling patterns; and (3) identify and classify patterns in farmers’ behavior regarding relevant factors in irrigation decision making.