Micro-irrigation can apply water with high uniformity. However, uniformity alone is not sufficient to achieve the goal of irrigation. Irrigation scheduling is equally important in micro-irrigation systems. The significance of various irrigation schedules and emitter flow uniformities were examined in a system design. Several irrigation schedules were compared with an optimal irrigation schedule. The optimal irrigation schedule can achieve optimal return and also provide water saving compared with the conventional irrigation schedule in which the whole field is fully irrigated at the same time. Deep seepage can be eliminated or minimised by scheduling deficit irrigation. An environmental protection irrigation schedule, where the whole field is in deficit, can save more water but will cause some reduction in total return compared to the optimal irrigation schedule. A simple irrigation schedule, in which the total amount of water applied is the same as the amount required, cannot only produce nearly optimal yield but also achieve increased water saving when high uniformity is also applied in the design. It is important to specify that the differences in total return and water saving between different schedules are reduced when high uniformity is applied in the design. For high uniformity the effects of crop sensitivity to deficit irrigation are not important and result in only limited (or acceptable) yield reduction and over-irrigation. Since a high proportion of water resources are used for agricultural production, micro-irrigation systems designed with high uniformity can be scheduled to achieve water conservation as well as environmental protection

Hydropower is considered a renewable form of energy production, but generating electricity from rivers is not always environmentally benign. The global demand for renewables is increasing rapidly as fossil fuels are gradually phased out, so rivers will continue to be subjected to the pressures imposed by hydropower for decades to come. Finding ways of operating hydropower plants that limit impacts on downstream river ecosystems is therefore a pressing global concern. Usually, these plants cause marked and rapid fluctuations in flow in downstream river reaches, termed ‘hydropeaking’. Hydropeaks result in a variety of ecological changes in the dynamic mountain rivers they typically affect; declines in fish and insect populations are evident, especially in reaches immediately downstream from the plant. While these changes are often acute and readily apparent, the underlying causal mechanisms remain unclear. We argue here that riverbed sediments are a critical but neglected causal link between hydropeaking flow regimes and ecological changes. We outline how a variety of tools from different branches of river science can now be brought together to understand precisely why hydropeaking alters sediment dynamics; these tools provide a mechanistic explanation for changes in bed sedimentary conditions and channel form across multiple scales and, consequently, a better understanding of ecological changes. By allowing us to simulate the effects of flow fluctuations on sediment dynamics and channel form, these tools also allow us to develop ways of releasing water from hydropeaking dams that limit impacts on aquatic habitat and species.

Exploring the realm of extreme weather events is indispensable for various engineering disciplines and plays a pivotal role in understanding climate change phenomena. In this study, we examine the ability of 10 probability distribution functions—including exponential, normal, two- and three-parameter log-normal, gamma, Gumbel, log-Gumbel, Pearson type III, log-Pearson type III, and SQRT-ET max distributions—to assess annual maximum 24 h rainfall series obtained over a long period (1972–2022) from three nearby meteorological stations. Goodness-of-fit analyses including Kolmogorov–Smirnov and chi-square tests reveal the inadequacy of exponential and normal distributions in capturing the complexity of the data sets. Subsequent frequency analysis and multi-criteria assessment enable us to discern optimal functions for various scenarios, including hydraulic engineering and sediment yield estimation. Notably, the log-Gumbel and three-parameter log-normal distributions exhibit superior performance for high return periods, while the Gumbel and three-parameter log-normal distributions excel for lower return periods. However, caution is advised regarding the overuse of log-Gumbel, due to its high sensitivity. Moreover, as our study considers the application of mathematical and statistical methods for the detection of extreme events, it also provides insights into climate change indicators, highlighting trends in the probability distribution of annual maximum 24 h rainfall. As a novelty in the field of functional analysis, the log-Gumbel distribution with a finite sample size is utilised for the assessment of extreme events, for which no previous work seems to have been conducted. These findings offer critical perspectives on extreme rainfall modelling and the impacts of climate change, enabling informed decision making for sustainable development and resilience.

This study presents the application of the finite element method integrated with Terzaghi’s principle. The definition of a model in oedometric or confinement conditions for settlement estimation of a building after the construction of a tunnel, including the effect of Terzaghi’s principle, is an unresolved problem. The objectives of this work include the demonstration of the need for a minimum of three methodological states to estimate said settlement. For this, a specific methodology is applied to a case study, with eight load steps and four types of coarse-grained soils. In the studied case, two layers of 50 m and 5 m with different degrees of saturation are overlaying an assumed impermeable rock layer. The excavation of a tunnel of 15 m in diameter at a depth of 30 m with drainage lining inside the tunnel is assumed. The minimum distance from the tunnel’s outline to the mat foundation is 15.8 m. It is determined that the settlement, according to Terzaghi’s principle, is around 11% of the total settlement for the most compacted soil types, reaching 35% for the loose soil type, from the tunnel’s outline. In the mat foundation, it implies an increase in the differential settlement of up to 12%. It shows a nonlinear relationship between some of the variables in the analysis. To detect the collapse due to uplifting the tunnel invert, it was determined that it was not appropriate to model in oedometric conditions. The novelty of the investigation relies on identifying and determining the need for a minimum of three states for methodological purposes for a proper quantification of the total settlement: (i) before the construction of the tunnel, (ii) immediately after the excavation of the tunnel, but without groundwater inflow into the tunnel, and (iii) after the tunnelling, with stabilised groundwater inflow into the tunnel.