Irrigation scheduling: a soft adaptor to weather uncertainties and irrigation efficiency improvement initiatives

Expanding dairy farming around the world including the Canterbury region of New Zealand is causing increasing demand for irrigation, placing more pressure on already stressed water resources. The challenge for New Zealand dairy farming is to maintain an appropriate equilibrium between pasture production and environment protection, achievable through the proper management/utilization of agricultural water, for which application and expansion of carefully identified and evaluated irrigation scheduling can play a key role. The focus of this research was, therefore, to contribute to the development of irrigation scheduling to determine the irrigation range within the soil water holding capacity taking into consideration precipitation (P), evapotranspiration (ET), plant available water (PAW) and crop coefficient (Kc). This was achieved through estimating Kc of pasture at different grazing rotations by field measurements and analysing irrigation and deep percolation under a range of PAW-based irrigation triggers by applications of mathematical modelling of irrigation scheduling. A farmers’ survey has been carried out with 32 dairy farmers in Canterbury, New Zealand to collect information on current irrigation practices, particularly in relation to PAW and grazing rotation. The experiments were conducted at Lincoln University Dairy Fram (LUDF), South Island, New Zealand during the period August 2014 to March 2016. A network of 20 non-weighing lysimeters and an Aquaflex installed on LUDF were utilized for the study. Pasture height, precipitation, irrigation application, deep percolation and change in soil moisture in the lysimeters were measured throughout the study period. Time Domain Reflectometry (TDR) probes with 200, 500 and 900 mm lengths were installed vertically adjacent to the Aquaflex and lysimeters for improving soil moisture determination in the lysimeters without disturbing natural water flux inside the lysimeters. To account for climatic variability, available 16 years of climatic data were collected from Broadfield weather station. Irrigation and deep percolation have been estimated using two soil-plant-atmosphere mathematical models (IrriCalc and CropWat 8) under a range of irrigation management strategies, including those identified in the farmers’ survey, and commonly applied crop coefficient values in addition to those estimated in this research. Based on reference and actual evapotranspiration, Kc of pasture was estimated for different grazing rotations. Analysing the relationship between Kc and crop canopy represented by pasture’s height (h in cm) showed that a linear fit simulates well this process. Aquaflex soil moisture (SM) readings resulted in a value of 0.43 for the coefficient of determination (R2) for the Kc – h relationship, which increased to 0.66 when Aquaflex SM measurements were adjusted for each lysimeter using corresponding TDR readings. This signifies the importance of accurate soil moisture determination to improve irrigation planning. The estimated values of Kc just after and before grazing were 0.6 and 1.0 for corresponding pasture heights of 10 cm and 30 cm. Average Kc for one grazing rotation was estimated at 0.7. This implies conventional irrigation planning with a constant pasture crop coefficient of 1.0 would provide “on average” 30% more water compared to the actual water demand of pasture under grazing condition. This significant amount of water saving can contribute to conserve water and reduce leaching of nutrients. During the shoulder seasons (September – October and March – May) current irrigation strategy leaves sufficient space for potential rain. However, during the peak irrigation season (November - February), the majority of farmers apply irrigation to fill soil up to 100% of the Field Capacity (FC), which is prone to cause deep percolation if rainfall follows an irrigation event. Analysis of the irrigation and deep percolation predicted for 14 irrigation seasons indicated that a minimum soil moisture level to start irrigation at 55 and 60 % of PAW, respectively on the shoulder and peak irrigation seasons, and stopping irrigation correspondingly at 80 and 90 % of PAW were optimal for this case study. This would allow for rainfall harvesting and thus, reduce net irrigation requirement and deep percolation losses. These results will make important contributions towards improving irrigation scheduling. Such irrigation scheduling can serve as soft adaptor to cope with weather uncertainty. The proposed irrigation scheduling contributes to agricultural water management, eventually supporting the sustainable development of dairy farming industries in New Zealand and around the world. In addition, it would also decrease water pollution by reducing nutrient leaching from pastoral farms to water resources

From Pre-Pandemic to Post-Pandemic Struggles to Meet Sustainable Development Goals

The need to achieve Sustainable Development Goals (SDGs) is universal for all high-, middle-, and low-income nations, but the momentum was disrupted by COVID-19. Tourism is an important sector to address SDGs where the United Nations World Tourism Organization (UNWTO) emphasizes the positive role tourism could play toward meeting those goals. This paper is conceptually grounded within the scope of the SDGs and uses a case study approach. It uses the case of Nepal, a developing country, to demonstrate the struggles of developing nations to meet SDGs within the context of the pandemic. Based on the literature and available secondary data, similar cases are discussed to establish relevance for global contexts by reflecting how other developing nations with troubled tourism ecosystems due to the pandemic will negatively impact the movement on meeting SDGs. Further, future directions are proposed to gain momentum toward responding to the SDGs. Indeed, developing nations will struggle more than others, as the priority has been to deal with the COVID-19 impacts with limited available resources

Wildlife Tourism Experiences at the Maasai Mara, Kenya: Using Kano Model to Assess Tourists’ Satisfaction

This study examines destination attributes through tourist reviews in the Maasai Mara ecosystem using the Kano model. Overall, positive reviews were dominant, and most tourists were satisfied with the Mara wildlife tourism experiences. However, some attributes led to dissatisfaction. The highest contribution to tourist satisfaction was due to excitement attributes such as witnessing the great migration of the wildebeest. Attributes such as safety and service-related aspects also negatively affected tourist satisfaction. The findings are useful in promoting sustainable wildlife tourism by government, private industry, and community-based tourism organizations

The mammalian LINC complex regulates genome transcriptional responses to substrate rigidity

Mechanical integration of the nucleus with the extracellular matrix (ECM) is established by linkage between the cytoskeleton and the nucleus. This integration is hypothesized to mediate sensing of ECM rigidity, but parsing the function of nucleus-cytoskeleton linkage from other mechanisms has remained a central challenge. Here we took advantage of the fact that the LINC (linker of nucleoskeleton and cytoskeleton) complex is a known molecular linker of the nucleus to the cytoskeleton, and asked how it regulates the sensitivity of genome-wide transcription to substratum rigidity. We show that gene mechanosensitivity is preserved after LINC disruption, but reversed in direction. Combined with myosin inhibition studies, we identify genes that depend on nuclear tension for their regulation. We also show that LINC disruption does not attenuate nuclear shape sensitivity to substrate rigidity. Our results show for the first time that the LINC complex facilitates mechano-regulation of expression across the genome

Improving irrigation water management using agent technology

Water use demand has increased steadily in Canterbury, New Zealand, over the last 20 years resulting in insufficient water availability. Prevailing irrigation management strategies in Canterbury consider soil moisture measurement up to a certain extent with no regard to crop’s development stages and sensitivity to water shortage; therefore, lacking to address the spatial and temporal variability of crop’s irrigation demand. This paper proposes an agent-based model that can be used to prioritise irrigation allocation to different crops on a farm. The proposed agent-based model takes into account the crop’s drought sensitivity, growth stage, soil type and the crop coefficient value when allocating water. It prioritises the crops based on their water requirements and generates an irrigation plan based on the predetermined water reduction. Our preliminary results showed that using this agent-based model, a significant water saving can be achieved even when water reduction is in effect, without impacting on production.The authors would like to extend their great gratitude to the Lincoln University, Christchurch, New Zealand for providing the required fund for the research

Investigating wind damage of centre pivot irrigators and farmers' reactions

In 2013 (September and October) Canterbury, New Zealand, observed devastating gales, with highly varied wind speeds ranging around 150–250 km h⁻¹. Over 800 centre pivot irrigators were damaged in just 2 days (10 and 11 September 2013). A second windstorm occurred on 14 October 2014, which exacerbated the situation. In 2014, Lincoln University conducted a survey of the farmers in Canterbury, New Zealand, to understand and investigate the windstorm damage to centre pivot irrigators and farmers' responses. There was a big difference between attitudes of farmers who either could or could not protect their irrigators. The majority of the farmers had limited information about their irrigators and they underestimated the windstorm. The windstorm damage occurred overnight, making it difficult to tackle the problem. The information from this study could contribute to developing an action plan to reduce windstorm damage on farms with centre pivot irrigators

Tour Guides’ Communication Ecosystems: An Inferential Social Network Analysis Approach

Successful performance by tour guides depends highly on their networking activities and interpersonal skills. Membership in related associations can provide opportunities for establishing and expanding a supportive network in the tour guiding profession. This study explores communication ecosystems used among the members of the largest professional tour guides organization, the World Federation of Tourist Guide Associations (WFTGA). Using the data collected from the 17th WFTGA convention in Tehran, Iran, we investigated five types of tour guides’ communications ecosystems (i.e. in-person, online-call, text-message, e-mail, and social networks) and compared them to tour guides’ networks of colleagues (i.e., the network that shows how people know one another and how they are linked). Moreover, we included the complementary no-contact network to enhance the internal validity of the study. Using exponential random graph modeling, all seven networks have been modeled using demographic characteristics such as age, gender, education, marital status, and tenure along with the history of participation in previous WFTGA conventions and WFTGA membership status. The analyses of virtual/digital (i.e., online-call, text-message, e-mail, and online social networks) and natural/traditional (i.e., in-person) communication ecosystems showed interesting similarities and differences among the seven networks, providing valuable insights for practitioners as well as academicians. Findings revealed the formation of networks based on homophily as well as heterophily effects is a function of types of communication ecosystem

Water distribution in community irrigation using a multi-agent system

Insufficient water for irrigation is a common problem in the Canterbury Region of New Zealand. Farmers have the option of applying for resource consent or joining a community irrigation scheme to take water. Water supply becomes more problematic during drought seasons as farmers must adhere to water restrictions imposed by the water authority. To deal with this problem, we developed an agent-based irrigation management system that can be used by farmers to calculate the ideal crop water needs on individual farms, which is particularly useful during periods of water scarcity. During water scarcity, most farms will have shortages of water. However, it is possible that there are farmers who will have excess water that could be distributed to those who need it. By doing this, farmers with excess water can make more profit and those who do not have enough water can purchase water to reduce their losses. In this work, we explore how auction-based negotiation in a multi-agent setting can be used to maximise water sharing within a community during periods of water scarcity. We evaluate various auction mechanisms that can be used to distribute excess water. In addition, we investigate the effect of various different agents' behaviours on water distribution and community profit

The Impact of Disasters on a Heritage Tourist Destination: A Case Study of Nepal Earthquakes

This study examines the degree of macroeconomic recovery of the Nepal tourism industry after a natural disaster using the autoregressive integrated moving average model (ARIMA). The study investigated the case of Nepal’s earthquakes in 2015 and examined the impact of the earthquakes on tourism inflows and GDP using time series data from 1990 to 2018. The results show that the increasing trend in the number of tourists changes in the post-earthquake period. In particular, the excess in tourist demand by age and purpose of visits after the earthquake indicates natural disaster as a potential reason for a tourism demand boost, often described as dark tourism in literature. This research shows the process of a heritage tourist destination assessing macroeconomic recovery from a natural disaster and fills the gap in the literature regarding purpose-based tourism demand and a link between dark tourism and disaster recovery on a heritage tourism destination