Small reservoirs play an important role in providing water to rural communities. Increased construction of small reservoirs to mitigate the effects of droughts leads to a High-density Reservoirs Network (HdRN) of small reservoirs, which can potentially modify the streamflows both in dry and wet periods. However, there is a lack of understanding of the interannual behavior of flow retention and the impact of future increases in the number of small reservoirs, mainly for HdRN in dryland catchments. This research aims to determine the possible impact of the increase in the number of small reservoirs on dry hydrological networks, evaluating the annual flows generated at the outlet of a dryland watershed for scenarios with different densities of small reservoirs (number of reservoirs per area). The study area was the Conceição river catchment (3347 km²) in the semiarid of Brazil. The hydrological model of the study area was developed in SWAT. The model obtained appropriate results for daily streamflows, with values of 0.63, 0.81, and 0.53% for NSE, KGE, and PBIAS, respectively. The current density of small reservoirs in the region was estimated at 0.068 reservoirs per square kilometer (res/km²). Eight expansion scenarios were defined for densities between 0.1 res/km² and 3.0 res/km². The results showed that the influence of the HdRN on runoff reduction mostly occurs for a probability of exceedance between 1% and 10% of month flows and is very small for months with very high peaks of flow. The reduction in the outlet flow due to the increase in the number of small reservoirs was stronger during dry years (up to 30%) than during wet years (up to 8%), and it tended to increase in years with a consecutive lack of rain (from about 7% in the first year to about 20% in the last year and in the worst scenario), which may intensify the period of extended droughts. This research provides insights about the impact of the increase in the number of small reservoirs on the interannual variability of flow retention, and the understanding of the influence of small reservoirs on runoff reduction may help water resources agencies better prepare for hydrologic extremes (droughts and floods).

Since ancient times, dams have been built to store water, control rivers, and irrigate agricultural land to meet human needs. By the end of the 19th century, hydroelectric power stations arose and extended the purposes of dams. Today, dams can be seen as part of the renewable energy supply infrastructure. The word dam comes from French and is defined in dictionaries using words like strange, dike, and obstacle. In other words, a dam is a structure that stores water and directs it to the desired location, with a dam being built in front of river valleys. Dams built on rivers serve various purposes such as the supply of drinking water, agricultural irrigation, flood control, the supply of industrial water, power generation, recreation, the movement control of solids, and fisheries. Dams can also be built in a catchment area to capture and store the rainwater in arid and semi-arid areas. Dams can be built from concrete or natural materials such as earth and rock. There are various types of dams: embankment dams (earth-fill dams, rock-fill dams, and rock-fill dams with concrete faces) and rigid dams (gravity dams, rolled compacted concrete dams, arch dams, and buttress dams). A gravity dam is a straight wall of stone masonry or earthen material that can withstand the full force of the water pressure. In other words, the pressure of the water transfers the vertical compressive forces and horizontal shear forces to the foundations beneath the dam. The strength of a gravity dam ultimately depends on its weight and the strength of its foundations. Most dams built in ancient times were constructed as gravity dams. An arch dam, on the other hand, has a convex curved surface that faces the water. The forces generated by the water pressure are transferred to the sides of the structure by horizontal lines. The horizontal, normal, and shear forces resist the weight at the edges. When viewed in a horizontal section, an arch dam has a curved shape. This type of dam can also resist water pressure due to its particular shape that allows the transfer of the forces generated by the stored water to the rock foundations. This article takes a detailed look at hydraulic engineering in dams over the millennia. Lessons should be learned from the successful and unsuccessful applications and operations of dams. Water resource managers, policymakers, and stakeholders can use these lessons to achieve sustainable development goals in times of climate change and water crisis.

From the perspective of the water–energy–food (WEF) security nexus, sustainable water-related infrastructure may hinge on multi-dimensional decision-making, which is subject to some level of uncertainties imposed by internal or external sources such as climate change. It is important to note that the impact of this phenomenon is not solely limited to the changing behavior patterns of hydro-climatic variables since it can also affect the other pillars of the WEF nexus both directly and indirectly. Failing to address these issues can be costly, especially for those projects with long-lasting economic lifetimes such as hydropower systems. Ideally, a robust plan can tolerate these projected changes in climatic behavior and their associated impacts on other sectors, while maintaining an acceptable performance concerning environmental, socio-economic, and technical factors. This study, thus, aims to develop a robust multiple-objective decision-support framework to address these concerns. In principle, while this framework is sensitive to the uncertainties associated with the climate change projections, it can account for the intricacies that are commonly associated with the WEF security network. To demonstrate the applicability of this new framework, the Karkheh River basin in Iran was selected as a case study due to its critical role in ensuring water, energy, and food security of the region. In addition to the status quo, a series of climate change projections (i.e., RCP 2.6, RCP 4.5, and RCP 8.5) were integrated into the proposed decision support framework as well. Resultantly, the mega decision matrix for this problem was composed of 56 evaluation criteria and 27 feasible alternatives. A TOPSIS/Entropy method was used to select the most robust renovation plan for a hydropower system in the basin by creating a robust and objective weighting mechanism to quantify the role of each sector in the decision-making process. Accordingly, in this case, the energy, food, and environment sectors are objectively more involved in the decision-making process. The results revealed that the role of the social aspect is practically negligible. The results also unveiled that while increasing the power plant capacity or the plant factor would be, seemingly, in favor of the energy sector, if all relevant factors are to be considered, the overall performance of the system might resultantly become sub-optimal, jeopardizing the security of other aspects of the water–energy–food nexus.

Optimizing water use efficiency and crop yield are important objectives of irrigated agriculture. For planning near future irrigation, farmers can rely on weather forecasts, which cover a time horizon of up to two weeks. This information is then used to make decisions about agricultural activities, including irrigation. However, a gap exists between weather forecasting and climate prediction, which poses challenges for decision-making in the medium-term crop season. The sub-seasonal to seasonal (S2S) range, spanning from two weeks to one season, bridges this gap. In this study we investigate if S2S forecasts combined with an agro-hydrological model can extend the time horizon of farmers’ decision decision-making compared to a traditional week-to-week schedule.A case study was conducted for the Northern German Hamerstorf experimental field, which is operated by the Chamber of Agriculture of Lower Saxony to provide weekly consulting and decision support services for regional farmers in the fields of fertilisation and irrigation. Irrigation is triggered at 35% and 50% of available water capacity and the annual crop yield for these irrigation scenarios is evaluated. In this research a SWAP (soil-water-atmosphere-plant) model was calibrated and validated using observed field data from the experiments. The calibrated model was then coupled with the reforecast S2S ensemble dataset. To evaluate the performance of the S2S/agro-hydrological model, we used the ECMWF (European Centre for Medium-Range Weather Forecasts) S2S ensemble and simulated the future irrigation water demand for the next two, four and six weeks. Simulated crop yield, irrigation water demand and the results of auto-scheduling irrigation over the recent five irrigation seasons (2018-2022) were evaluated and compared with a reanalysis using observed climate and with the experimental field practise.First results confirm that uncertainty increases with the lead time of the forecast, but a major aspect for irrigation planning is the start and end of dry periods. There, uncertainty is less compared to the uncertainty of future rain, which recommends further exploration of the value of S2S forecasts in agricultural decision support.

The Muskingum routing method involves the calculation of the storage volume in river reaches. The accurate calculation of the storage volume is difficult to achieve with the nonlinear Muskingum model (NMM). This paper couples the storage moving average (SMA) with NMM to produce a Muskingum storage moving average model (MUSSMAM), which has improved the accuracy of storage volume and output hydrograph calculation over the NMM. The parameters of the NMM and the weighting coefficients in the SMA are treated as dimensionless parameters in the combined MUSSMAM formulation. A hybrid method that merges the generalized reduced gradient (GRG) solver with an evolutionary (EV) solver is employed to obtain the best combination of parameter values of the MUSSMAM. The sum of the squared deviation (SSQ) between observed and routed inflows is the objective function optimized with the hybrid GRG-EV solver. The proposed MUSSMAM is tested with experimental, real, and multimodal hydrograph-routing problems. These resu...