Irrigation and Ecosystem Services: development of an irrigation model for the LUCI ecosystem services framework

<p>Poor water quality is currently a major environmental issue worldwide and in New Zealand, where reactive Nitrogen (N) and Phosphorous (P) lost from agricultural fields are significant drivers of water quality degradation in rural catchments. Irrigation application to crops is essential to agricultural production however irrigation inputs can increase N and P losses to waterways via drainage and/or overland flow directly and as a result of reduced soil capacity to buffer rainfall events. Indirect nutrient losses are also increased following irrigation implementation due to amplified farming intensity. Furthermore, irrigation applications represent the world’s greatest consumptive use of water. Improving irrigation efficiency with regard to water use represents a synergistic opportunity for the improvement of a number of different ecosystem services including water quality, water supply, and food production. Spatially explicit modelling of irrigation is needed to determine inefficiencies in water delivery and target these inefficiencies for management or mitigation at sub-field scales. A complimentary need exists for irrigation modelling within ecosystem service decision support tools so that nutrient and water movement can be accurately quantified in irrigated environments. This thesis describes the development and implementation of SLIM – the Spatially-explicit LUCI Irrigation Model. SLIM adapts existing lumped hydrological and irrigation modelling techniques and practices to a fully distributed, spatially explicit framework, so that sub-field variations in water flows resulting from variable soil properties are accounted for. SLIM is generally applicable across New Zealand, using readily available national scale datasets and literature derived parameters. SLIM is capable of predicting irrigation depth and timing based on common management strategies and irrigation system characteristics, or can replicate irrigation applications where information is available. Outputs from SLIM are designed to assist irrigation management decisions at the field level, and to inform the hydrology component of the Land Utilisation and Capability Indicator (LUCI) ecosystem service assessment framework. Standalone SLIM outputs include time-series files, water balance plots, and raster maps describing the efficiency and efficacy of the modelled irrigation system. SLIM has been applied in three different agroecosystems in New Zealand under surface, micro, and spray irrigation systems, each characterised by different levels of data availability. Results show that SLIM is able to accurately predict the timing of irrigation applications and provide usable information to inform irrigation application decisions. SLIM outputs emphasise the importance of soil variability with regard to water loss and risk of nutrient leaching. Opportunity exists for irrigation water use efficiency to be improved through targeted management at sub-field scales in New Zealand farming systems.</p>

Irrigation and Ecosystem Services: development of an irrigation model for the LUCI ecosystem services framework

<p>Poor water quality is currently a major environmental issue worldwide and in New Zealand, where reactive Nitrogen (N) and Phosphorous (P) lost from agricultural fields are significant drivers of water quality degradation in rural catchments. Irrigation application to crops is essential to agricultural production however irrigation inputs can increase N and P losses to waterways via drainage and/or overland flow directly and as a result of reduced soil capacity to buffer rainfall events. Indirect nutrient losses are also increased following irrigation implementation due to amplified farming intensity. Furthermore, irrigation applications represent the world’s greatest consumptive use of water. Improving irrigation efficiency with regard to water use represents a synergistic opportunity for the improvement of a number of different ecosystem services including water quality, water supply, and food production. Spatially explicit modelling of irrigation is needed to determine inefficiencies in water delivery and target these inefficiencies for management or mitigation at sub-field scales. A complimentary need exists for irrigation modelling within ecosystem service decision support tools so that nutrient and water movement can be accurately quantified in irrigated environments. This thesis describes the development and implementation of SLIM – the Spatially-explicit LUCI Irrigation Model. SLIM adapts existing lumped hydrological and irrigation modelling techniques and practices to a fully distributed, spatially explicit framework, so that sub-field variations in water flows resulting from variable soil properties are accounted for. SLIM is generally applicable across New Zealand, using readily available national scale datasets and literature derived parameters. SLIM is capable of predicting irrigation depth and timing based on common management strategies and irrigation system characteristics, or can replicate irrigation applications where information is available. Outputs from SLIM are designed to assist irrigation management decisions at the field level, and to inform the hydrology component of the Land Utilisation and Capability Indicator (LUCI) ecosystem service assessment framework. Standalone SLIM outputs include time-series files, water balance plots, and raster maps describing the efficiency and efficacy of the modelled irrigation system. SLIM has been applied in three different agroecosystems in New Zealand under surface, micro, and spray irrigation systems, each characterised by different levels of data availability. Results show that SLIM is able to accurately predict the timing of irrigation applications and provide usable information to inform irrigation application decisions. SLIM outputs emphasise the importance of soil variability with regard to water loss and risk of nutrient leaching. Opportunity exists for irrigation water use efficiency to be improved through targeted management at sub-field scales in New Zealand farming systems.</p>

Optimizing Tomato Growth and Productivity Using Nitrogen and Irrigation Application Timing

Soil nutrients and water management practices according to the concept of 4R nutrient stewardship (right rate, right timing, right placement, and right source) can have significant benefits on crop productivity and reduce the negative effects of agricultural practices on the environment. Therefore, this present study evaluated the effects of nitrogen (N) application timing under different irrigation regimes on open-field, fresh-market tomato production in Florida. In this study, 2 N application timings applied at 25% pre-plant with 75% fertigation (BM), and 0 pre-plant with 100% fertigation (NB), were evaluated. The two N application methods were evaluates using three irrigation regimes: full irrigation (FI, 100% ETc), deficit irrigation (DI, 66% ETc), and regulated deficit irrigation (RDI, 66% ETc during the first 4 weeks after transplanting and 100% ETc afterward). The results showed that BM treatment significantly improved early-season tomato growth compared to NB treatment. The results also indicated that under RDI and DI irrigation conditions, tomato root length was lowest (average value of 13%) within the first 15 cm compared to 40% within 15–30 cm and 47% at 30–40 cm soil depths. Similar to plant growth, BM treatment significantly increased tomato yield (average valued 56.00 Mg ha−1) compared to the NB (average value 40.23 Mg ha−1). The application of DI throughout the growing season reduced tomato yield; however, there were no differences in yield under the RDI and FI irrigation regimes. Therefore, based on the results from this study, it can be concluded that, under Florida growing conditions, pre-plant N application is essential for tomato growth and productivity. Additionally, irrigation application using the RDI method could be successfully adopted in Florida tomato production for improved water savings without any negative effects on tomato growth and productivity.

BIOMETRIC CHARACTERISTICS OF 'CATHERINE SEL 1' PEACH CULTIVAR IN SEMIARID ENVIRONMENT

In arid and semi-arid regions, irrigation application is mandatory for modern fruit growing, but the optimal irrigation application requires large amounts of water. In the context of global warming, water saving is a major objective. Therefore, deficit irrigation (DI) is an attractive alternative. The plant studied was thirteen years old ‘Catherine Sel.1’ peach trees. The trees were grafted on franc rootstock and planted in a 4 m x 3 m layout. Soil management was represented by clean cultivation both between tree rows and in the row. Fruit size and weight are important qualities and yield traits in peach (Prunus persica (L) Batsch), but the factors that influence fruit size and weight remain to be explored. The fruit biometrical characteristics was influenced by the irrigation regime, with the irrigated treatment with 100% AHI (T1) showing significantly (P <5%) higher differences versus T2 and T3. As with fruit biometrical characteristics, the fruit weight determined on the fruits of the studied treatments had the same trend. In this study, we investigated the impact of stress hydric on fruit size and weight at 'Catherine sel 1' peach cultivar in 2019-2020 period.

Methods for Strawberry Transplant Establishment in Florida

Florida is the second largest strawberry producer in the United States, with an annual farm gate value of about $300 million. Planting occurs from late September through late October, and high air temperatures pose significant challenges for transplant establishment and thus yield and fruit quality. The primary purpose of this new 4-page publication of the UF/IFAS Horticultural Sciences Department is to provide research-based recommendations on transplant establishment methods for strawberry growers in Florida. The techniques presented are overhead irrigation application methods and practices, strawberry plugs and bare-root transplants, crop protectants, and reflective mulching. Written by Emmanuel Torres-Quezada, Lincoln Zotarelli, Vance M. Whitaker, and Shinsuke Agehara.https://edis.ifas.ufl.edu/hs1376