Hydrology and water quality impacts of alternative land management practices are poorly quantified for semi-arid environments in the northern Australia cropping zone, yet wide-scale changes in tillage practices and land use were being recommended based on experience from other environments. The objective of this study was to explore changes in soil profile and catchment hydrology and water quality associated with different soil surface conditions created by different tillage and grazing practices. Soil water, runoff, and suspended sediment concentrations were monitored on 4 contour bay catchments over an 18-year period. Soil conditions were described by soil moisture, soil cover, and surface roughness in order to explore functional relationships between management, hydrology, and water quality. The site was chosen to represent the drier margins of cropping in southern Queensland where clay soils with high water-holding capacity, in conjunction with fallowing to store water for later crop growth, are an essential risk management tool. Accumulation of soil water in fallows was inefficient, with fallow efficiencies ranging from –7 to 40% due to high evaporation and runoff losses. Runoff amount was determined by soil water content, which was strongly influenced by antecedent rainfall, water use, and evaporation patterns. Surface cover and roughness had subtle influences on runoff, and a greater effect on suspended sediment concentration. Runoff and suspended sediment losses were considerably lower under pasture than cropping. A participative approach between farmers and scientists was demonstrated to be an efficient method to carry out an extensive and long-term catchment study at a remote location. This study provides benchmark data for future hydrologic and water quality investigations.

Cropping systems in south-eastern Queensland have led to degradation of soil physical properties and loss of infiltration capacity. Pasture leys are favoured for ameliorating soil physical properties because they add organic matter to the soil, create macroporosity, and help to re-aggregate soil. We measured change in hydraulic conductivity with period of ley for 5 major soil groups in south-eastern Queensland (Sodosols, light and heavy Vertosols, Red Ferrosols, and Red Chromosols/Kandosols). We characterised 2 soil layers that are susceptible to degradation when cropped: surface soil exposed to raindrop impact, and the layer immediately below the cultivated layer (0·1-0·2 m deep). A rainfall simulator was used to measure hydraulic conductivity of surface seals under high intensity rainfall. Disc permeameters and pressure plate apparatus were used to measure hydraulic conductivity of the soil matrix in the 0·1-0·2 m layer. Hydraulic conductivity of both soil layers improved with period of pasture for all but the light-textured Red Chromosols/Kandosols. The estimated period of pasture required to return hydraulic conductivity to pre-cultivated levels ranged from 5 to 40 years, depending on soil type and layer. This is about 2-3 times the period of cultivation that caused the degradation. Grazing reduced the effectiveness of pasture in ameliorating surface sealing on Sodosols. Beneficial effects of a 2·5-4·5 year, ungrazed ley pasture on surface soil persisted for up to 5 years after recultivation, but were lost in the 0·1-0·2 m layer within 1 year. These rates of decline in hydraulic conductivity were faster than observed on previously uncultivated soils. The APSIM model was used to predict the effect of measured improvements in soil hydraulic conductivity on average runoff from summer fallows. The model predicted that most benefits for fallow runoff would be achieved with 2-5 years of ley. The surface seal was the major limitation to infiltration when the soil was bare. Subsurface soil layers limited infiltration if surface sealing was reduced by ameliorating soil properties or maintaining cover on the soil surface. The results suggest that despite amelioration of soil structure with leys, appropriate tillage and cover management is still required to maintain high infiltration rates.

In making irrigation decisions, farmers typically rely on local observation and experience, such as observing crops and neighbors’ actions. Research has mainly focused on understanding crop water requirements to improve farming practices, but it is important to acknowledge that farmers have unique perspectives, access to diverse local “signals”, and experience. The challenge is to strike a balance between complex technical assessments of field conditions (the science) and harnessing farmers’ skills to manage their irrigation in ways that maximize yield and quality. This study established a basis for specifying minimum data requirements for pragmatic, but not necessarily perfect, irrigation decision-making for small-scale Vietnamese coffee farmers. This study focuses on three areas in Dak Lak province in the Central Highlands of Vietnam. To explore the role of monitoring in irrigation management, two contrasting monitoring systems were set up to collect soil, weather, and irrigation data. We also compared a variety of water balance models with different data requirements, with a focus on processes that used “passive data collection”, i.e., farmers do not manually collect data, rather data can be accessed readily from external sources. In Vietnam, traditional hosepipe irrigation is applied where it is impractical to know the volume of applied water. The proposed Low Data Model (LDM) is suited to more informed irrigation scheduling decisions, which have potential to improve the likelihood of coffee growers adopting measurement-based decision-making. While researchers may seek a detailed daily sub-millimeter understanding of soil water dynamics, farmers require practical decision support if there is to be any adoption of improved methods. This study offers a simple and practical approach for irrigation scheduling rather than a model using numerically perfect data that is unachievable in the field. The work demonstrates that on-site rainfall data is essential. However, other data can be collected passively to reduce the burden of data collection on users. This approach may enhance the likelihood of model-based irrigation scheduling being adopted by coffee farmers in Vietnam.

Australian agriculture managers deal with climates that are characterised by high variability and unpredictability. A simple framework for decision-making is used to structure weather-related inquiries using recent and long-term climate data to better inform decisions based on current conditions and future expectations. This paper describes the rationale, design philosophy, and development journey of Australian CliMate (CliMate), a contemporary climate analysis tool built to consolidate and modernise the functionality of earlier computer-based decision support tools (DSTs). CliMate aimed to be simple, transparent, and user-driven, supporting tactical and strategic agricultural decisions. Ten core analyses were included from previous DSTs. With over 20,000 registered users and widespread adoption among farmers, consultants, and other professionals over a decade, CliMate demonstrates the enduring demand for accessible, mobile climate analysis tools. We reflect on lessons learned in the development process, advocating for minimalism, iteration with users, and integration of transparent data sources. This experience underscores the necessity for long-term support and evaluation to sustain the value of agricultural DSTs.