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Tipping bucket rain gauges (TBRs) continue to be one of the most widely used pieces of equipment for rainfall monitoring; they are frequently used for the calibration, validation, and downscaling of radar and remote sensing data, due to their major advantages—low cost, simplicity and low-energy consumption. Thus, many works have focused and continue to focus on their main disadvantage—measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks' operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques, summarizing TBR measurement uncertainties, focusing on calibration and error reduction strategies, discussing the state of the art and providing future perspectives of the technology. [ABSTRACT FROM AUTHOR]

Highlights • Satellite images have been utilized to estimate crop coefficients. • The estimated and the theoretical crop coefficients have been compared. • The comparison was made among field plots, municipalities and irrigation districts. • A set of water use efficiency indicators have been calculated. Abstract Irrigation in the Duero river basin accounts for 75% of total water resources. Nevertheless, irrigation in this area is paramount to maintain agricultural production. Within this context, this paper is aimed at assessing the water use efficiency (WUE), for the major crop (corn), among four irrigation districts (IDs) from 2014 to 2017. Since the WUE indicators base upon crop water requirements, these were calculated by estimating the reference evapotranspiration and the local crop coefficients Kc. First, they were estimated by satellite images and then, compared with the recommendation from the Regional Irrigation Advisory Service. Finally, the gross irrigation requirements were compared with the irrigation supply. WUE indicators varied among IDs depending upon the hydrologic year, the water available for irrigation (superficial and subsurface water), and the corn sowing date. Usually, the IDs performed deficit irrigation in the dry years, and either full irrigation or over irrigation in the wet years. The rainfall only fulfilled less than 10% of corn requirements. Small differences in Kc were observed within municipalities (in each ID) and/or among IDs. The pattern of the Kc fitted curves varied among IDs and was affected by sowing dates. Although, the local Kc values were close to the general coefficients recommended by the Irrigation Advisory Service, they affected the determination of gross irrigation requirements which were significant different among IDs. Moreover, it was observed that the FAO recommendation for the duration of the corn growth stages fitted better the estimated Kc than the one from the Advisory Center. The gross irrigation requirements were similar among IDs and years, varying between 6476 and 7646 m3/ha. The local Kc estimation could help irrigation managers to adapt the irrigation supply to the actual corn needs. [ABSTRACT FROM AUTHOR]

Currently, basins monitoring is carried out extensively principally in large basins with low spatial sensors distribution. The low distribution is lower in developing countries due mainly to the monitoring process' cost, not just the acquisition cost of the equipment but also the data transmission and equipment maintenance.Basins and water resources management depend on the acquisition of reliable hydrometeorological data, even more in small mountain basins in semi-arid areas. These basins are vulnerable to drastic changes, in relief, elevation, vegetation and soils, which generates high hydrometeorological variability in short distances, causing high floods and fast floods events.This framework highlights that the necessity to increase sensors density in catchments would be possible if their monitoring is efficient at low cost, especially in small mountain basins. This work proposes a hydrometeorological monitoring for small catchments which is based on low cost sensors, electronics and programming on free software and hardware Arduino. It could be an alternative to traditional monitoring with commercial instruments and software.The proposal is based on three sensorisation units that allows to measure climatic variables such as precipitation, relative humidity and temperature; edaphological variables such soil moisture content and hydrological variables such as surface runoff from the water depth measurement. In addition, the proposal includes data transmission units, data logging and equipment powered unit. To allow and almost real time data acquisition, data protection and autonomy in the operation of the system.The selected equipment for this proposal has been evaluated and validated preliminarily in the laboratory condition, obtaining satisfactory results, that promises, is possibility of hydrometeorological variables measurement and monitoring, spatially in small mountain basins with a good accuracy and at a cheapest way. Next step is to try it in field conditions. [ABSTRACT FROM AUTHOR]

A novel methodology for the optimal placement of sensors in watercourses is presented. The methodology aimed at finding the optimal locations for the placement of sensors to maximize the amount of information to monitor flow and velocity in watercourses. The methodology is based on the maximization of the Gram determinant of the sensor responses at each possible location or a combination of locations. Two illustrative examples are presented wherein locations for one- and two-sensor cases for the velocity and flow monitoring of the Venero Claro River Basin, Spain, are selected. The kinematic wave method was used to evaluate the sensor response at every possible location. The results confirm the suitability of this methodology for finding the optimal locations for sensors to monitor flow or velocity in watercourses. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to assess spatial and temporal irrigation performance in urban parks and can assist park manager/operator decisions in irrigation management. First, irrigation needs are estimated by traditional irrigation scheduling and the irrigation zones with similar water needs that share the same electric valve (hydrozones) are identified. Then, irrigation performance is calculated using the relative water supply (RWS) indicator and mapped (GIS software). This approach can be adapted to various spatial and temporal scales. In this study, it was applied to the Valdebebas urban development VBB (Madrid) between the 2017 and 2019 irrigation seasons. The results for the VBB parks showed high spatio-temporal variation in irrigation performance among plant typologies within an irrigation season, which can be explained by the landscape coefficient KL variation across the parks. Likewise, this variation was also observed among the three evaluated seasons; explained among other factors by differences in irrigation management. For each hydrozone, the estimation of the NDVI index by Sentinel-2A satellite images in 2019 showed a threshold on irrigation performance. Thus, the remote sensing data together with the proposed approach can be a valuable tool for helping park managers/technicians adopt better decisions on irrigation practices. [ABSTRACT FROM AUTHOR]