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Studies conducted at the field scale report significant reductions in the irrigation requirements of rice when continuous submergence (CS) is replaced by less water-demanding regimes such as flush-irrigation (FI, i.e. intermittent irrigations of rice growing in non-submerged soils). However, the effects of their extensive application in paddy areas with shallow groundwater is much less studied. We present a scenario analysis investigating the impacts on irrigation requirements induced by a shift from CS to FI in an irrigation district of Northern Italy where rice is the main crop, followed by maize and poplar. The area is characterised by a shallow water Table whose depth fluctuates between two meters (in winter) and less than 1 m (in summer). We applied a three-stage procedure, where we first analysed present state conditions using the SWAP (Soil, Water, Atmosphere, Plant) model to simulate irrigation deliveries and percolation fluxes. Then, we calibrated an empirical relationship between estimated percolation fluxes and measured depths to groundwater. Finally, we applied this relationship, in combination with the SWAP model, to predict the variation of district irrigation requirements due to a widespread shift from CS to FI. Results show that neglecting the feedback between groundwater recharge due to irrigation and groundwater depth led to overestimating the reduction of irrigation requirements of rice, which decreased from around 80% when no feedback was considered to around 60% when it was accounted for. Moreover, increased groundwater depths resulted in higher irrigation requirements for maize with an estimated growth of more than 50% due to the need of shortening the irrigation turn. These results demonstrate the importance of considering the impacts on the hydrological processes at larger scales when planning the conversion of CS into more efficient field irrigation methods.

Modern and effective water management in large alluvial plains that have intensive agricultural activity requires the integrated modeling of soil and groundwater. The models should be complex enough to properly simulate several, often non-linear, processes, but simple enough to be effectively calibrated with the available data. An operative, practical approach to calibration is proposed, based on three main aspects. First, the coupling of two models built on wellvalidated algorithms, to simulate (1) the irrigation system and the soil water balance in the unsaturated zone and (2) the groundwater flow. Second, the solution of the inverse problem of groundwater hydrology with the comparison model method to calibrate the model. Third, the use of appropriate criteria and cross-checks (comparison of the calibration results and of the model outputs with hydraulic and hydrogeological data) to choose the final parameter sets that warrant the physical coherence of the model. The approach has been tested by application to a large and intensively irrigated alluvial basin in northern Italy.

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ABSTRACT:The time series of measurements of hydro-meteorological variables often suffer from imperfections such as missing data, outliers and discontinuities in the mean values. The discontinuity in the mean can be the effect of: instrumental offsets and of their corrections, of changes in the monitoring station or in the surrounding environment. If the discontinuities can be identified with a reasonable precision, a correction of the erroneous data can be made. Several authors have put their great effort into developing techniques to identify non-climatic inhomogeneities; the resulting statistical methods are especially effective when the series contains a single change point, while their performances decline when the series contains multiple change points or inhomogeneous segments (a portion of the series bounded by two complementary shifts). These limitations also affect the standard normal homogeneity test (SNHT), one of the most effective and widely applied tests. We present a composite method of homogeneity testing, standard normal homogenization composite method (SNHCM), including the SNHT as one component, which improves the SNHT performances with multiple change points and inhomogeneous segments. A number of comparisons among the new method, the SNHT and a powerful optimal segmentation method (OSM-CM), are illustrated in the paper. SNHCM demonstrates their performances in change-point detection similar to, or better than, the SNHT and very close to the OSM-CM. The SNHCM is effective in recognizing complex patterns of discontinuities, especially inhomogeneous segments, which represent a severe problem for SNHT; on the contrary, SNHT performs slightly better only when the series contains a single change point, but the difference between the two methods is negligible. Compared to the OSM-CM, SNHCM provides very similar performances, with some favourable features deriving from the fact that it is computationally lighter, simpler to implement, can easily handle very long series and is based on statistical hypothesis tests with a well-defined and adjustable significance level.

The cultivation of rice, one of the most important staple crops worldwide, has very high water requirements. A variety of irrigation practices are applied, whose pros and cons, both in terms of water productivity and of their effects on the environment, are not completely understood yet. The continuous monitoring of irrigation and rainfall inputs, as well as of soil water dynamics, is a very important factor in the analysis of these practices. At the same time, however, it represents a challenging and costly task because of the complexity of the processes involved, of the difference in nature and magnitude of the driving variables and of the high variety of field conditions. In this paper, we present the prototype of an integrated, multisensor system for the continuous monitoring of water dynamics in rice fields under different irrigation regimes. The system consists of the following: (1) flow measurement devices for the monitoring of irrigation supply and tailwater drainage; (2) piezometers for groundwater level monitoring; (3) level gauges for monitoring the flooding depth; (4) multilevel tensiometers and moisture sensor clusters to monitor soil water status; (5) eddy covariance station for the estimation of evapotranspiration fluxes and (6) wireless transmission devices and software interface for data transfer, storage and control from remote computer. The system is modular and it is replicable in different field conditions. It was successfully applied over a 2-year period in three experimental plots in Northern Italy, each one with a different water management strategy. In the paper, we present information concerning the different instruments selected, their interconnections and their integration in a common remote control scheme. We also provide considerations and figures on the material and labour costs of the installation and management of the system.

Water use efficiencies (WUEs) between 20% and 60% are commonly reported for single rice paddies. When larger spatial domains are considered, higher WUE than minimum values observed for individual fields are expected due to water reuse. This study investigates scale-effects on water balances and WUEs of four adjacent rice fields located in Northern Italy and characterized by different elevations (A ≅ B + C > D). Water balance terms for the paddies were quantified during the agricultural season 2015 through the integrated use of observational data and modelling procedures. Following a Darcy-based approach, percolation was distinguished from net seepage. Results showed net irrigation of about 2,700 and 2,050 mm for fields A and B, and around 640 and nearly 0 mm for C and D. WUE of A, B, C and D amounted, respectively, to 21, 28, 66 and >100%. Values for C and D were due to less permeable soils, to seepage fluxes providing extra water inputs and to the shallow groundwater level. When the group of paddies ACD was considered (B was not included since it was separated by a deep channel), net irrigation and WUE were found to reach 1,550 mm and 39%, confirming the important role of water reuses in paddy agro-ecosystems.

European rice production is concentrated in limited areas of a small number of countries. Italy is the largest European producer with over half of the total production grown on an area of 220,000 hectares, predominantly located in northern Italy. The traditional irrigation management (wet seeding and continuous flooding until few weeks before harvest—WFL) requires copious volumes of water. In order to propose effective ‘water-saving’ irrigation alternatives, there is the need to collect site-specific observational data and, at the same time, to develop agro-hydrological models to upscale field/farm experimental data to a spatial scale of interest to support water management decisions and policies. The semi-distributed modelling system developed in this work, composed of three sub-models (agricultural area, groundwater zone, and channel network), allows us to describe water fluxes dynamics in rice areas at the irrigation district scale. Once calibrated for a 1000 ha district located in northern Italy using meteorological, hydrological and land-use data of a recent four-year period (2013–2016), the model was used to provide indications on the effects of different irrigation management options on district irrigation requirements, groundwater levels and irrigation/drainage network efficiency. Four scenarios considering a complete conversion of rice irrigation management over the district were implemented: WFL; DFL—dry seeding and delayed flooding; WDA—alternate wetting and drying; WFL-W—WFL followed by post-harvest winter flooding from 15 November to 15 January. Average results for the period 2013–2016 showed that DFL and WDA would lead to a reduction in summer irrigation needs compared to WFL, but also to a postponement of the peak irrigation month to June, already characterized by a strong water demand from other crops. Finally, summer irrigation consumption for WFL-W would correspond to WFL, suggesting that the considered winter flooding period ended too early to influence summer crop water needs.