Poor management of nitrogen (N) fertilisers and water in agro-ecosystems reduces yield, quality and N-use efficiency, and leads to pollution. The objective of this study was to improve irrigation and N management for planted pastures through adaptive management with simple tools and modelling. Field experiments were conducted in 2007 and 2008 at Cedara (KwaZulu Natal) and Hatfield (Gauteng) using annual ryegrass as a case study under a range of N and irrigation application strategies. Collected data sets were also used to calibrate and validate the SWB-Pro (simple) and SWB-Sci (detailed) model versions. After validation, the model was used to develop irrigation calendars and strategies, and estimate irrigation requirements for annual ryegrass. The highest forage yields were produced when N application rates ranged between 30 to 60 kg N ha-1 for each growth cycle, except for the first 2-3 growth cycles when there was high soil N carryover from the previous season. The current farmers’ recommendation (fixed N application rate of 50 kg ha-1 per growth cycle) maximised biomass but reduced pasture quality. Adaptive strategies based on nitrate concentration in wetting front detectors at different depths, reduced fertiliser N application by 28–32% and reduced potentially leachable residual soil N, while improving forage quality without yield reduction. The rate 30-40 kg N ha-1 per growth cycle provided a compromise between forage yield and quality. The SWB model performed well in simulating ryegrass growth, leaf area index, forage yield, root zone soil water deficit, daily evapotranspiration, biomass N uptake and soil nitrate. Site specific and monthly variable irrigation calendars were developed using the SWB-Pro model, for four major milk producing areas of South Africa. The simpler monthly irrigation calendars can be used in the absence of irrigation monitoring tools or more accurate site specific calendars. The SWB-Pro model requires relatively few and simple inputs. However, irrigation monitoring/scheduling with the aid of real time modelling or measurements is better than calendars developed using the SWB-Pro model with long-term historical weather data. The SWB-Sci model showed ways of improving water use efficiency using ‘room for rain’ and ‘mildly deficit irrigation’ approaches in high rainfall areas. Scenario modelling demonstrated that the best management strategy of achieving maximum yield together with low N leaching is by integrating N and water management. This integrated management can be based on the wetness of the soil and nitrate concentration in the deep root zone using wetting front detectors. The model can be used to generate monitoring protocols such as depth of wetting front detector placement and selecting N thresholds to be used for adaptive management. Setting approximate thresholds for wetting depth and nitrate concentration is a first step in implementing an adaptive management strategy. However, the challenge is to find monitoring tools which allow effective implementation of the strategy. In this study, the wetting front detector proved to be a robust, on-farm water and nitrate monitoring tool which is relatively simple and cost effective. Should it become widely adopted, farmers are expected to improve these thresholds as more experience is gained. The SWB model could also be used to evaluate alternative thresholds for adaptive N and water management. / Thesis (PhD)--University of Pretoria, 2012. / Plant Production and Soil Science / unrestricted

The current study has been conducted in response to the growing problem of water scarcity and the need for more effective methods of irrigation water management. Remote sensing techniques have been used to match spatially and temporally distributed crop water demand to water application rates. Remote sensing approaches using Landsat imagery have been applied to estimate the components of a soil water balance model for an agricultural field by determining daily values of surface/root-zone soil moisture, evapotranspiration rates, and losses and by developing a forecasting model to generate optimal irrigation application information on a daily basis. Incompatibility of coarse resolution Landsat imagery (30m by 30m) with heterogeneities within the agricultural field and potential underestimation of field variations led the study to its main objective, which was to develop models capable of representing spatial and temporal variations within the agricultural field at a compatible resolution with farming management activities. These models support establishing real-time management of irrigation water scheduling and application. The AggieAirTM Minion autonomous aircraft is a remote sensing platform developed by the Utah Water Research Laboratory at Utah State University. It is a completely autonomous airborne platform that captures high-resolution multi-spectral images in the visual, near infrared, and thermal infrared bands at 15cm resolution. AggieAir flew over the study area on four dates in 2013 that were coincident with Landsat overflights and provided similar remotely sensed data at much finer resolution. These data, in concert with state-of-the-art supervised learning machine techniques and field measurements, have been used to model surface and root zone soil volumetric water content at 15cm resolution. The information provided by this study has the potential to give farmers greater precision in irrigation water allocation and scheduling.

This study evaluated the impacts of shallow and deep open drains on groundwater levels and drain performance under varying climate scenarios and irrigation application rates. The MIKE SHE model used for this study is an advanced and fully spatially distributed hydrological model. Three drain depths, climates and irrigation application rates were considered. The drains depths included 0, 1 and 2 m deep drains. The annual rainfall and meteorological data were collected from study area from 1976 to 2004 and analysed to identify the typical wet, average and dry years within the record. Similarly three irrigation application rates included 0, 10 and 16 ML/ha-annum. All together twenty seven scenarios (3 drains depths, 3 climates and 3 irrigation application rates) were simulated. The observed soil physical and hydrological data were used to calibrate and validate the model. Mean square error (R[superscript]2) of the simulated and observed water table data varied from 0.7 to 0.87. Once validated the MIKE SHE model was used to evaluate the effectiveness of 1 and 2 metre deep drains. The simulated water table depth, unsaturated zone deficit, exchange between unsaturated and saturated zones, drain outflow and overland flow were used to analyse their performance. The modeling results showed that the waterlogging was extensive and prolonged during winter months under the no drainage and no irrigation scenario. In the wet climate scenario, the duration of water logging was longer than in the average climate scenario during the winter months. In the dry climate scenario no waterlogging occurred during the high rainfall period. The water table reached soil surface during the winter season in the case of wet and average climate. For the dry climate, the water table was about 0.9 metres below soil surface during winter. / One and 2 metre deep drains lowered the water table up to 0.9 and 1.8 metres in winter for the wet climate when there was no irrigation application. One metre deep drains proved effective in controlling water table during wet and average climate without application of irrigation water. One metre deep drains were more effective in controlling waterlogging a in wet, average and dry years when the irrigation application rate was 10 ML/ha-annum. With 16 ML/ha-annum irrigation application, 1 metre deep drains did not perform as efficiently as 2 metre deep drains in controlling the water table and waterlogging. In the dry climate scenario, without irrigation application, 1 metre deep drains were not required as there was not enough flux from rainfall and irrigation to raise the water table and create waterlogging risks. Two metre deep drains lowered the water table to greater depths in the wet, average and dry climate scenarios respectively when no irrigation was applied. They managed water table better in wet and average climate with 10 and 16 ML/ha-annum irrigation application rate. Again in the dry climate, without irrigation application 2 metre deep drains were not required as there was a minimal risk of waterlogging. The recharge to the groundwater table in the no drainage case was far greater than for the 1 and 2 metre deep drainage scenarios. The recharge was higher in case of 1 metre deep drains than 2 metre deep drains in wet and average climate during winter season. / There was no recharge to ground water with 1 and 2 metre deep drains under the dry climate scenarios and summer season without irrigation application as there was not enough water to move from the ground surface to the unsaturated and saturated zones. When 10 ML/ha-annum irrigation rate was applied during wet, average and dry climate respectively, 1 metre deep drains proved enough drainage to manage the recharge into the groundwater table with a dry climate. For the wet and average climate scenarios, given a 10 ML/ha-annum irrigation application rate, 2 metre deep drains managed recharge better than 1 metre deep drains. Two metres deep drains with a 10 ML/ha-annum irrigation application rate led to excessive drainage of water from the saturated zone in the dry climate scenario. Two metres deep drains managed recharge better with a 16 ML/ha-annum irrigation application rate in the wet and average climate scenarios than the 1 metre deep drains. Two metres deep drains again led to excessive drainage of water from the saturated zone in dry climate. In brief, 1 metre deep drains performed efficiently in the wet and average climate scenarios with and without a 10 ML/ha-annum irrigation application rate. One metre deep drains are not required for the dry climate scenario. Two metre deep drains performed efficiently in the wet and average climate scenarios with 16 ML/ha-annum irrigation application rate. Two metre deep drains are not required for the dry climate scenario.