Sustainability of irrigated agriculture under salinity pressure – A study in semiarid Tunisia

In semiarid and arid Tunisia, water quality and agricultural practices are the major contributing factors to the degradation of soil resources threatening the sustainability of irrigation systems and agricultural productivity. Nowadays, about 50% of the total irrigated areas in Tunisia are considered at high risk for salinization. The aim of this thesis was to study soil management and salinity relationships in order to assure sustainable irrigated agriculture in areas under salinity pressure. To prevent further soil degradation, farmers and rural development officers need guidance and better tools for the measurement, prediction, and monitoring of soil salinity at different observation scales, and associated agronomical strategy. Field experiments were performed in semi-arid Nabeul (sandy soil), semi-arid Kalâat Landalous (clay soil), and the desertic Fatnassa oasis (gypsiferous soil). The longest observation period represented 17 years. Besides field studies, laboratory experiments were used to develop accurate soil salinity measurements and prediction techniques. In saline gypsiferous soil, the WET sensor can give similar accuracy of soil salinity as the TDR if calibrated values of the soil parameters are used instead of standard values. At the Fatnassa oasis scale, the predicted values of ECe and depth of shallow groundwater Dgw using electromagnetic induction EM-38 were found to be in agreement with observed values with acceptable accuracy. At Kalâat Landalous (1400 ha), the applicability of artificial neural network (ANN) models for predicting the spatial soil salinity (ECe) was found to be better than multivariate linear regression (MLR) models. In semi-arid and desertic Tunisia, irrigation and drainage reduce soil salinity and dilute the shallow groundwater. However, the ECgw has a larger impact than soil salinity variation on salt balance. Based on the findings related to variation in the spatial and temporal soil and groundwater properties, soil salinization factors were identified and the level of soil “salinization risk unit” (SRU) was developed. The groundwater properties, especially the Dgw, could be considered as the main cause of soil salinization risk in arid Tunisia. However, under an efficient drainage network and water management, the soil salinization could be considered as a reversible process. The SRU mapping can be used by both land planners and farmers to make appropriate decisions related to crop production and soil and water management

Drainage models: an evaluation of their applicability for the design of drainage systems in arid regions

Only 5%–10% of irrigated lands in least developed countries (LDCs) are currently drained. Although drainage simulation models (DSMs) are used to evaluate alternative designs, it is unclear which drainage model is suitable for LDCs' arid and semi-arid regions. This study evaluates selected DSMs (ADAPT, RZWQM2, DRAINMOD, EPIC, HYDRUS-1D, WaSim and SWAP) and critically assesses their applicability to arid and semi-arid areas. Also, establish and apply selection criteria based on the availability of data in LDCs with Libya as a case study, and identify the most suitable model for application in Libya. DRAINMOD had the highest overall score, and alternative methods to predict missing input parameters for DRAINMOD are discussed. Evaluating the feasibility of using predicted input parameters for DSMs to design drainage systems in LDCs would help farmers, planners and decision-makers to reduce the overall cost of drainage system and, also, make DRAINMOD a more accessible tool to evaluate different drainage designs

Application of artificial neural networks to the design of subsurface drainage systems in Libyan agricultural projects

Study region The study data draws on the drainage design for Hammam agricultural project (HAP) and Eshkeda agricultural project (EAP), located in the south of Libya, north of the Sahara Desert. The results of this study are applicable to other arid areas. Study focus This study aims to improve the prediction of saturated hydraulic conductivity (Ksat) to enhance the efficacy of drainage system design in data-poor areas. Artificial Neural Networks (ANNs) were developed to estimate Ksat and compared with empirical regression-type Pedotransfer Function (PTF) equations. Subsequently, the ANNs and PTFs estimated Ksat values were used in EnDrain software to design subsurface drainage systems which were evaluated against designs using measured Ksat values. New hydrological insights Results showed that ANNs more accurately predicted Ksat than PTFs. Drainage design based on PTFs predictions (1) result in a deeper water-level and (2) higher drainage density, increasing costs. Drainage designs based on ANNs predictions gave drain spacing and water table depth equivalent to those predicted using measured data. The results of this study indicate that ANNs can be developed using existing and under-utilised data sets and applied successfully to data-poor areas. As Ksat is time-consuming to measure, basing drainage designs on ANN predictions generated from alternative datasets will reduce the overall cost of drainage designs making them more accessible to farmers, planners, and decision-makers in least developed countries

Calibration of DRAINMOD for prediction of water table depths and drain discharges under waterlogged Vertisols of Maharashtra, India

An estimation of optimal design parameters of subsurface drainage system through monitoring of water table depths and drain discharges are expensive in terms of time and money. The simulation modeling is an effective tool for estimation of drainage design parameters at less cost and short time. In view to this, calibration of DRAINMOD model for prediction of water table depths and drain discharges were conducted by installing subsurface drainage system with 40 m drain spacing and 1.0 m drain depth at Agricultural Research Station, Kasbe Digraj, Dist. Sangli (Maharashtra) during 2012-13 to 2013-14. The field data on water table depth and drain discharge were used for calibration of DRAINMOD model. The input data files on climatic, soil, crop and drainage design system parameters were attached to DRAINMOD model and calibrated successfully. It is found that both observed and simulated water table depths and drain discharges showed a fluctuating trend and predicted both water table depths and drain discharges closely with the observed values during frequent rainy days and following the rainy days. The DRAINMOD model reliably predicted water table depths with a goodness of fit (R2 = 0.97), MAE (12.23 cm), RMSE (15.49 cm) and CRM (0.05); drain discharges with R2 of  0.93, MAE of 0.095 mm day-1, RMSE of 0.1876 mm day-1and CRM of 0.04. Thus, the calibrated DRAINMOD model can be used to simulate the water table depths and drain discharges in semi-arid climatic conditions of Maharashtra and in turn to estimate and evaluate drain spacing and depth

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Study of the Soil Water Movement in Irrigated Agriculture

In irrigated agriculture, the study of the various ways water infiltrates into the soils is necessary. In this respect, soil hydraulic properties, such as soil moisture retention curve, diffusivity, and hydraulic conductivity functions, play a crucial role, as they control the infiltration process and the soil water and solute movement. This Special Issue presents the recent developments in the various aspects of soil water movement in irrigated agriculture through a number of research topics that tackle one or more of the following challenges: irrigation systems and one-, two-, and three-dimensional soil water movement; one-, two-, and three-dimensional infiltration analysis from a disc infiltrometer; dielectric devices for monitoring soil water content and methods for assessment of soil water pressure head; soil hydraulic properties and their temporal and spatial variability under the irrigation situations; saturated–unsaturated flow model in irrigated soils; soil water redistribution and the role of hysteresis; soil water movement and drainage in irrigated agriculture; salt accumulation, soil salinization, and soil salinity assessment; effect of salts on hydraulic conductivity; and soil conditioners and mulches that change the upper soil hydraulic properties and their effect on soil water movement

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.A In order to promote irrigation sustainability through reporting by irrigation water managers around Australia, we have developed an adaptive framework and methodology for improved triple-bottom-line reporting. The Irrigation Sustainability Assessment Framework (ISAF) was developed to provide a comprehensive framework for irrigation sustainability assessment and integrated triple-bottom-line reporting, and is structured to promote voluntary application of this framework across the irrigation industry, with monitoring, assessment and feedback into future planning, in a continual learning process. Used in this manner the framework serves not only as a "reporting tool", but also as a "planning tool" for introducing innovative technology and as a "processes implementation tool" for enhanced adoption of new scientific research findings across the irrigation industry. The ISAF was applied in case studies to selected rural irrigation sector organisations, with modifications to meet their specific interests and future planning

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Since 3000 BC, rice has been the main crop in the Korean Peninsula, and where currently most of the available irrigation water is used to grow paddy rice. Methods for calculating the quantity of irrigation water required developed in the 1990's were compared to quantities measured in the field. The largest difference between calculated and measured quantities occurred in April and May. Based on field data we obtained in the middle part of the Korean Peninsula, significant changes have occurred in rice management, which has changed the amount of irrigation water required. Rice is now transplanted earlier, and duration of the transplanting phase on the regional scale is shorter through mechanization and consolidation of land holdings. These changes need to be taken into account when calculating the quantity of water needed for irrigation

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Experiences establishing Water User Associations (WUAs) in Egypt have been carried out for the past 15 years, with increasingly promising results. Most of these activities have been pilot projects aiming to demonstrate the benefits and sustainability of WUAs. They were consequently implemented through a centralized and resource-intensive process and focused on limited numbers of associations. Since 2003, the Ministry of Water Resources and Irrigation (MWRI) has adopted as policy the large-scale development of Branch Canal WUAs. With support from USAID, about 600 branch canal WUAs (BCWUAs) have since been established, covering 15% of Egypt's irrigated area and involving half a million farmers and residents. In order to achieve this impressive outcome, a different approach has been developed and implemented, emphasizing the direct involvement of MWRI field staff and a partnership between water users and MWRI managers. This paper also argues that the conventional approach of forming WUAs by focusing on water users, and empowering them to take over the O&M responsibilities of irrigation systems, is not adapted to the Egyptian context