Daniele Zaccaria

Flexible delivery schedules to improve farm irrigation and reduce pressure on groundwater: a case study in southern Italy

This study was conducted on an irrigated area of southern Italy to analyze the current operation of a large-scale irrigation delivery system and the effects of the operation procedures on crop irrigation management and aquifer salinity increase. The area is characterized by relatively high levels of groundwater salinity in the summer that are probably due to intensive groundwater pumping by farmers during periods of peak irrigation demand, with the resulting seawater intrusion. Two alternative delivery schedules, namely the rotation delivery schedule and the flexible delivery schedule, referred to as RDS and FDS, respectively, were simulated using a soil-water balance model under different combinations of crop, soil and climatic conditions. The first set of simulations concerned the farm irrigation management constrained by the rotational delivery used by the local water management organization. The second scenario simulated the farm irrigation schedule most commonly used by growers in the area for maximizing crop yields. Based on crop irrigation management under RDS and FDS, two alternative operational scenarios were also developed at the scheme level and then compared for evaluation. Winter and summer salinity maps of the aquifer were developed by interpolating salinity measurements of the groundwater samples collected during the 2006 irrigation season. From these maps, a close relationship can be inferred among delivery schedule, aquifer exploitation and salinity increase, which justifies the need for implementing FDS that might reduce the groundwater demand for irrigation.

Evapotranspiration Estimate over an Almond Orchard Using Landsat Satellite Observations

California growers face challenges with water shortages and there is a strong need to use the least amount of water while optimizing yield. Timely information on evapotranspiration (ET), a dominant component of crop consumptive water use, is critical for growers to tailor irrigation management based on in-field spatial variability and in-season variations. We evaluated the performance of a remote sensing-based approach, Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), in mapping ET over an almond orchard in California, driven by Landsat satellite observations. Reference ET from a network of weather stations over well-watered grass (ETo) was used for the internal calibration and for deriving ET at daily and extended time period, instead of alfalfa based reference evapotranspiration (ETr). Our study showed that METRIC daily ET estimates during Landsat overpass dates agreed well with the field measurements. During 2009–2012, a root mean square error (RMSE) of 0.53 mm/day and a coefficient of determination (R2) of 0.87 were found between METRIC versus observed daily ET. Monthly ET estimates had a higher accuracy, with a RMSE of 12.08 mm/month, a R2 of 0.90, and a relatively small relative mean difference (RMD) of 9.68% during 2009–2012 growing seasons. Net radiation and Normalized Difference Vegetation Index (NDVI) from remote sensing observations were highly correlated with spatial and temporal ET estimates. An empirical model was developed to estimate daily ET using NDVI, net radiation (Rn), and vapor pressure deficit (VPD). The validation showed that the accuracy of this easy-to-use empirical method was slightly lower than that of METRIC but still reasonable, with a RMSE of 0.71 mm/day when compared to ground measurements. The remote sensing based ET estimate will support a variety of State and local interests in water use and irrigation management, for both planning and regulatory/compliance purposes, and it provides the farmers observation-based guidance for site-specific and time-sensitive irrigation management.

Modeling delivery performance in pressurized irrigation systems from simulated peak-demand flow configurations

Abstract A methodology to assess performance of pressurized irrigation distribution networks is presented, which is based on generation of flow configurations from simulated delivery scenarios, and on subsequent analysis of network operation and delivery achievements. The rationale of the methodology entails simulating the peak-demand flow configurations in the pipe network through a deterministic–stochastic combined agro-hydrological model, and forecasting the delivery performance by means of a hydraulic simulation model and of some specific performance indicators. The agro-hydrological model generates disaggregated information on soil water deficits for all the cropped fields downstream from the delivery hydrants, and forecasts the demand flow hydrographs and irrigation deliveries for the entire service area during peak-demand periods. The simulated-demand flow configurations are then passed on to the hydraulic simulation model, which evaluates the hydraulic performance achievable by the pipe network. The performance analysis is then refined using additional indicators specifically adapted to pressurized irrigation networks. The proposed methodology was applied to a large-scale pressurized irrigation system of southern Italy that is in need of modernization. Results proved the usefulness of the combined use of simulation tools as components of an analytical framework to address modernization and re-engineering of existing irrigation delivery networks, on the basis of targeted delivery performance.

Simulation of peak-demand hydrographs in pressurized irrigation delivery systems using a deterministic–stochastic combined model. Part II: model applications

This study describes a model named HydroGEN that was conceived for simulating hydrographs of daily volumes and hourly flow rates during peak-demand periods in pressurized irrigation delivery networks with on-demand operation. The model is based on a methodology consisting of deterministic and stochastic components and is composed of a set of input parameters to reproduce the crop irrigation management practices followed by farmers and of computational procedures enabling to simulate the soil water balance and the irrigation events for all cropped fields supplied by each delivery hydrant in a distribution network. The input data include values of weather, crop, and soil parameters, as well as information on irrigation practices followed by local farmers. The resulting model outputs are generated flow hydrographs during the peak-demand period, which allow the subsequent analysis of performance achievable under different delivery scenarios. The model can be applied either for system design or re-design, as well as for analysis of operation and evaluation of performance achievements of on-demand pressurized irrigation delivery networks. Results from application of HydroGEN to a real pressurized irrigation system at different scales are presented in a companion paper (Part II: model applications).

Irrigation Delivery Performance and Environmental Externalities from a Risk Assessment and Management Perspective

© 2012 Zaccaria and Passarella, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Irrigation Delivery Performance and Environmental Externalities from a Risk Assessment and Management Perspective