Elsevier

Biosystems Engineering

Volume 93, Issue 3, March 2006, Pages 335-346
Biosystems Engineering

A Simulation Model to generate the Demand Hydrographs in Large-scale Irrigation Systems

https://doi.org/10.1016/j.biosystemseng.2005.12.006Get rights and content

The study reports the development of a model for the generation of daily volumes and hourly discharge hydrographs, withdrawn from on-demand pressurised irrigation systems. The model is based on the simulation of the water budget at the level of each single hydrant. Under the hypothesis that the initial soil moisture is at field capacity, once the soil water reserve falls down a pre-defined limit value, irrigation occurs. The farmer's management strategy was simulated using a stochastic approach allowing for the generation of the initial time of each irrigation at each hydrant. The aggregation of the hydrant hydrographs generates the discharge hydrographs at the upstream end of the network. The calibration of the model was carried out comparing the generated and measured hydrographs at the upstream end of an irrigation network in Southern Italy. The results obtained are satisfactory even though they require further verifications. The comparison has generally shown a good correspondence, particularly for daily withdrawn volumes. The simulated hourly discharges showed, sometimes, hourly peaks higher than the measured ones. The proposed model, when well calibrated, can be used for the design of new irrigation systems as well as for the analysis of existing ones.

Introduction

Large pressurised irrigation systems allow for better services and higher distribution efficiency as compared to open channel systems. Systems operating on-demand offer the greatest opportunity to meet irrigation requirements as farmers decide when and how much water to take from the network (Labye et al., 1988; Lamaddalena & Sagardoy, 2000). A number of preliminary conditions have to be satisfied: (i) an adequate water tariff of withdrawn volumes, (ii) delivery devices equipped with flowmeter, flow limiter, pressure control and gate valve, and (iii) an adequate design for conveying the demand discharge during the peak period by delivering the minimum pressure head at hydrants for on-farm irrigation equipment.

One of the most important uncertainties in an on-demand system is the calculation of the discharges from the network. As farmers control the irrigation, it is impossible to know, a priori, the hydrants operating simultaneously. In such systems, the nominal discharge attributed to each hydrant is much greater than the expected share, so that the hydrant operates for less than 24 h. As a result, the probability of all hydrants being open simultaneously is very low. Thus, it would not be reasonable to design the network for a discharge equal to the sum of the hydrants capacities. These considerations have justified the use of probabilistic approaches for computing the discharges in on-demand systems. However, variabilities related to the discharges flow occur in such systems in relation to scheduling decisions over time depending on the cropping pattern, crops grown, meteorological conditions, on-farm efficiency and management strategy. These variabilities may produce failures related to the design options. Therefore, designers and managers should have an adequate knowledge of the hydraulic behaviour of the system.

The advent of on-demand large-scale irrigation systems in the early 1960s, in France, fostered the development of statistical models to compute the design flows. Examples of such models are the first and the second formula of Clément (1966). Although these models are theoretically sound, the assumptions governing the determination of the parameters do not take into account the actual functioning of an irrigation system.

In view of these limitations, a number of researchers tackled the problem by simulating irrigation strategies (CTGREF, (1974), CTGREF, (1977); Béthery, 1990; Lamaddalena & Ciollaro, 1993). Maidment and Hutchinson (1983) modelled the demand pattern over a large irrigation area taking into account the size of the irrigated area, the soil type, the cropping pattern, the irrigation strategy and the weather variation. However, the demand hydrograph had to be averaged out over time in order to avoid unrealistic water demands, which were very high one day and very low the next day. Abdellaoui (1986) proposed a demand model based on the queuing theory. The model generated irrigation water demand hydrographs at any node of an irrigation system by maintaining the soil water balance. This model allowed the determination of the design capacity of an irrigation system, but it is difficult to apply to an on-demand pressurised system because of the short time steps required.

The queuing theory does not consider the farmer's management strategy, nor the topographic location of the hydrants. Fields are usually irrigated even when the system is saturated, with a pressure lower than the minimum required for an appropriate on-farm operation, and hydrants located on a favourable topographic site receive first water despite the queue order, because of the low head the requirement.

The Environmental Protection Agency (EPA) of the United States has developed a model called EPANET (Rossman et al., 1993; Rossman 2000), that performs an extended period simulation of hydraulic and water quality behaviour within pressurised pipe networks. This software requires the demand hydrograph at each node as an input data and does not generate it. Teixeira et al. (1995) presented a simulation model to calculate the crops irrigation requirements in the peak period according to the soil type, the cropping pattern, the irrigation method efficiency and the percentage of the irrigated area. The main interest of this model is the possibility of simulating several scenarios and, therefore, allowing the identification of appropriate design conditions, which may be found in order to improve flexibility in operation and management activities. The model does not compute the discharges flowing into the irrigation network.

Walker et al. (1995) developed the Command Area Decision Support Model (CADSM) for estimating an aggregated demand and studying management options for irrigated areas. Daily water and salt balances are simulated for individual fields within command areas based on crop type and stage of development, field characteristics, soil properties, possible groundwater contribution, salinity level and several queuing factors that take cultural practices into account. The model was developed to assist irrigation project managers in operating surface irrigation systems at the command area level.

Lamaddalena (1997) and Lamaddalena and Sagardoy (2000) developed a new integrated methodology for the optimisation and the performance analysis of on-demand irrigation systems considering the several flow regime (SFR) approach. The model requires, as an input, the upstream peak discharge to generate randomly the corresponding configurations of hydrants simultaneously operating and, therefore, the discharges flowing into the network sections.

D’Urso (2001) proposed an integrated and deterministic model to simulate the demand in an on-demand irrigation system, assuming that the hydrograph is limited by the hydraulic capacity of the network, using remote-sensing techniques to evaluate the spatial variability of the water deficit of the cropping system.

All the above shows that the existing models do not generate information on the multiple discharges that can flow into the irrigation network and, consequently, when used at the design stage, they do not assure the conditions for a good performance of the irrigation distribution network during its life-span.

In this paper, a model based on the soil water balance is presented for generating in an on-demand large-scale irrigation system both the demand hydrographs at the hydrant level and at the upstream end of the distribution network, which can be used for the design of new distribution networks as well as for the analysis of the existing ones. The model considers the deterministic component represented by the equation of soil water balance and the stochastic component function of the uncertainties linked to the sowing date of the crops, the initial water reserve and the farmer's management strategy. For a better clarification of the model, it is presented through an application to an irrigation network in Southern Italy.

Section snippets

Modelling approach

For the period between sowing and harvesting, daily soil water balance was estimated at each single hydrant in the irrigation distribution network. Each hydrant was set to irrigate a maximum of three different crops or fields.

Once the water demand at each hydrant was known, the demand at the upstream end of the distribution network was determined by aggregating the demands at the hydrants up to the system level.

Description of the district irrigation system

The model has been applied and tested on an irrigation district of the Sinistra Ofanto scheme in the province of Foggia (Italy), by comparing measured and simulated withdrawn volumes and hourly discharges.

The irrigation scheme is managed by the consortium of Capitanata and covers about 22 500 ha (CBC, 1984; Altieri, 1995). It is divided into seven districts, each of them being sub-divided into sectors. Table 2 shows the actual cropping pattern of the district under study.

A daily storage and

Results and discussion

The application of the methodology to the irrigation network under study allowed the generation of the applied daily irrigation volumes and the upstream peak discharges. Figure 9 shows a good fitting achieved between the registered and the simulated irrigation volumes considering ten irrigation seasons from 1990 to 1999. Figure 10 shows a comparison between the hourly registered and simulated discharges hydrographs day per day for the identified 10-day peak period of 1999. For the entire

Conclusion

A soil water balance model (SWBM) was developed to aggregate the crop-irrigation requirements, to generate the discharges hydrographs and to assist design and management options of on-demand irrigated districts.

Daily water balances are simulated for individual fields within the irrigation districts based on daily weather and rainfall data, crop type and stage of development, irrigation methods and soil properties. The irrigation requirements for individual fields are aggregated to estimate

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