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An ever-increasing number of rainfall estimates is available. They are used in many important applications such as flood/drought monitoring, water management, or climate monitoring. Such data are especially valuable in sub-Saharan Africa, where rainfall has considerable socioeconomic impacts and the gauge and radar networks are sparse. The choice of a rainfall product can significantly influence the performance of such applications. This study reviews previous works, evaluating or comparing rainfall products over different parts of sub-Saharan Africa. Three types of rainfall products are considered: the gauge-only, the satellite-based, and the reanalysis ones. In addition to the global rainfall products, we included three regional ones specifically developed for Africa: the African Rainfall Climatology version 2 (ARC2), the Rainfall Estimate version 2 (RFE2), and the Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) African Rainfall Climatology and Time Series (TARCAT). The gauge density, the orography, and the rainfall regime, which vary with the climate and the season, influence the performance of the rainfall products. This review does not focus on comparing results, as many other publications doing so are already available. Instead, we propose this review as a guide through the different rainfall products available over Africa, and the factors influencing their performances. With this review, the reader can make informed decisions about which products serve their specific purpose best. [ABSTRACT FROM AUTHOR]

Food and economic security in West Africa rely heavily on rainfed agriculture and are threatened by climate change and demographic growth. Accurate rainfall information is therefore crucial to tackling these challenges. Particularly, information about the occurrence and length of droughts as well as the onset date of the rainy season is essential for agricultural planning. However, existing rainfall models fail to accurately represent the highly variable and sparsely monitored West African rainfall patterns. In this paper, we show the potential of deep learning (DL) to model rainfall in the region and propose a methodology to develop DL models in data-scarce areas. We built two DL models for satellite rainfall (rain/no-rain) detection over northern Ghana from Meteosat TIR data based on standard DL architectures: Convolutional neural networks (CNNs) and convolutional long short-term memory neural networks (ConvLSTM). The Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) and Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System (PERSIANN-CCS) products are used as benchmarks. We use rain gauge data from the Trans-African Hydro-Meteorological Observatory (TAHMO) for model development and performance evaluation. We show that our models compare well against existing products despite being considerably simpler, developed with a small training dataset—i.e., 8 stations covering 2.5 years with 20.4% of the data missing—and using TIR data alone. Concretely, our models consistently outperform PERSIANN-CCS for rain/no-rain detection at a sub-daily timescale. While IMERG is the overall best performer, the DL models perform better in the second half of the rainy season despite their simplicity (i.e., up to 120 k parameters). Our results suggest that DL-based regional models are a promising alternative to state-of-the-art global products for providing regional rainfall information, especially in meteorologically complex regions such as the (sub)tropics, which are poorly covered by ground-based rainfall observations. [ABSTRACT FROM AUTHOR]

Highlights: [•] Information-theoretical method for weighting ensemble forecasts. [•] Enables incorporation of new information in existing ensemble. [•] Ensures that uncertainty is not reduced more than permitted by forecast information. [•] Comparison with other weighting methods. [•] Based on Jaynes’s principle of maximum entropy. [ABSTRACT FROM AUTHOR]

From algorithmic information theory, which connects the information content of a data set to the shortest computer program that can produce it, it is known that there are strong analogies between compression, knowledge, inference and prediction. The more we know about a data generating process, the better we can predict and compress the data. A model that is inferred from data should ideally be a compact description of those data. In theory, this means that hydrological knowledge could be incorporated into compression algorithms to more efficiently compress hydrological data and to outperform general purpose compression algorithms. In this study, we develop such a hydrological data compressor, named HydroZIP, and test in practice whether it can outperform general purpose compression algorithms on hydrological data from 431 river basins from the Model Parameter Estimation Experiment (MOPEX) data set. HydroZIP compresses using temporal dependencies and parametric distributions. Resulting file sizes are interpreted as measures of information content, complexity and model adequacy. These results are discussed to illustrate points related to learning from data, overfitting and model complexity. [ABSTRACT FROM AUTHOR]

Climate change is exacerbating adverse impacts of water stress in rainfed agriculture. This paper seeks to identify safe sowing windows for smallholder farmers in the Sudanian region of West Africa (WA). We hypothesize that the traditional focus on the onset of the season to start sowing leads to crop losses in years of high rainfall intermittency. AquaCrop, an FAO crop model, is used to simulate the yield response of maize (Zea mays L.) to sowing dates ranging from the 1st of May to the 30th of November at 20 locations in WA. We find that sowing directly after the first rains carries a higher risk of water stress, hampering crop development due to insufficient buildup of soil water storage to overcome dry spells. Based on three years of data per station on average, we identify safe sowing windows across the Sudanian region that secure optimal yield in 97% of all cases. We find that delaying sowing to mid-June (savanna and western part of the region) and to July (semi-arid region) ensures optimal yields. Of the three commonly applied local onset approaches covered in our evaluation, only LO10mm (10 mm/day on four consecutive days) achieves a similar yield result. The advantage of the safe window approach is that it is accessible for smallholders, who in many cases do not have access to local rainfall information. [ABSTRACT FROM AUTHOR]

argued that computational hydrology can only be a proper science if the hydrological community makes sure that hydrological model studies are executed and presented in a reproducible manner. Hut, Drost and van de Giesen replied that to achieve this hydrologists should not "re-invent the water wheel" but rather use existing technology from other fields (such as containers and ESMValTool) and open interfaces (such as the Basic Model Interface, BMI) to do their computational science. With this paper and the associated release of the eWaterCycle platform and software package (available on Zenodo: 10.5281/zenodo.5119389,), we are putting our money where our mouth is and providing the hydrological community with a "FAIR by design" (FAIR meaning findable, accessible, interoperable, and reproducible) platform to do science. The eWaterCycle platform separates the experiments done on the model from the model code. In eWaterCycle, hydrological models are accessed through a common interface (BMI) in Python and run inside of software containers. In this way all models are accessed in a similar manner facilitating easy switching of models, model comparison and model coupling. Currently the following models and model suites are available through eWaterCycle: PCR-GLOBWB 2.0, wflow, Hype, LISFLOOD, MARRMoT, and WALRUS While these models are written in different programming languages they can all be run and interacted with from the Jupyter notebook environment within eWaterCycle. Furthermore, the pre-processing of input data for these models has been streamlined by making use of ESMValTool. Forcing for the models available in eWaterCycle from well-known datasets such as ERA5 can be generated with a single line of code. To illustrate the type of research that eWaterCycle facilitates, this paper includes five case studies: from a simple "hello world" where only a hydrograph is generated to a complex coupling of models in different languages. In this paper we stipulate the design choices made in building eWaterCycle and provide all the technical details to understand and work with the platform. For system administrators who want to install eWaterCycle on their infrastructure we offer a separate installation guide. For computational hydrologists that want to work with eWaterCycle we also provide a video explaining the platform from a user point of view (https://youtu.be/eE75dtIJ1lk , last access: 28 June 2022)​​​​​​​. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both Open Science and FAIR science. [ABSTRACT FROM AUTHOR]

Abstract: Flooding is the most devastating natural hazard in Pakistan and the recent flooding has demonstrated its severeness. Floods are common throughout the country. However, their characteristics differ from region to region. Flooding behavior of the major basins and flood management at the national level are investigated in this article. Monsoon rainfalls are the main source of floods in the Indus Basin, while Mediterranean Waves and Cyclones, which are generated over the Arabian Sea, induce flooding in the Kharan Basin and the Makran Coastal Area. Fluvial floods in the Indus Basin have caused major economic losses. Pakistan’s government has spent vast resources on relief operations and flood works since the country came into existence in 1947. A number of provincial and federal acts, ordinances, accords, and treaties shape the national flood policy. Institutional setup for flood hazard and crisis management has evolved over the years. Nevertheless, data show no major reduction in the flood-to-damage ratio. The inter-linkage of structural and non-structural measures and their combined efficiency must be analyzed and optimized for more effective flood management. [Copyright &y& Elsevier]

Over the past five years, Distributed Temperature Sensing (DTS) along fiber optic cables using Raman backscattering has become an important tool in the environmental sciences. Many environmental applications of DTS demand very accurate temperature measurements, with typical RMSE < 0.1 K. The aim of this paper is to describe and clarify the advantages and disadvantages of double-ended calibration to achieve such accuracy under field conditions. By measuring backscatter from both ends of the fiber optic cable, one can redress the effects of differential attenuation, as caused by bends, splices, and connectors. The methodological principles behind the double-ended calibration are presented, together with a set of practical considerations for field deployment. The results from a field experiment are presented, which show that with double-ended calibration good accuracies can be attained in the field. [ABSTRACT FROM AUTHOR]

Abstract: This article provides an overview of both experimental and modeling research carried out over the past 15 years by the authors addressing scaling effects in Hortonian surface runoff. Hortonian surface runoff occurs when rainfall intensity exceeds infiltration capacity of the soil. At three sites in West Africa (Côte d’Ivoire, Ghana, and Burkina Faso) runoff was measured from plots of different lengths to assess scale effects. Consistently, longer plots showed much lower runoff percentages than shorter plots. There were large variations in runoff percentages from one rainstorm to the next but there were very good correlations between plots of equal length for each single event. This strongly suggests that temporal dynamics are the cause behind the observed scale effects. In the literature, spatial variability is often proffered as explanation for such scale effects without providing a mechanism that would cause consistent reduction in runoff percentages with increasing slope length. To further examine whether temporal dynamics can indeed provide the explanation, Hortonian runoff was simulated using models with increasing levels of complexity. The simplest model was already able to reproduce the observed scale effects. Also more complex models were used that accounted explicitly for spatial variability. The conclusions remained the same regarding the role of temporal dynamics. Finally, a dimensional analysis was developed that helps predict under which circumstances one can expect scale effects similar to the ones observed in West Africa. [Copyright &y& Elsevier]

Recently, an information-theoretical decomposition of Kullback--Leibler divergence into uncertainty, reliability, and resolution was introduced. In this article, this decomposition is generalized to the case where the observation is uncertain. Along with a modified decomposition of the divergence score, a second measure, the cross-entropy score, is presented, which measures the estimated information loss with respect to the truth instead of relative to the uncertain observations. The difference between the two scores is equal to the average observational uncertainty and vanishes when observations are assumed to be perfect. Not acknowledging for observation uncertainty can lead to both overestimation and underestimation of forecast skill, depending on the nature of the noise process. [ABSTRACT FROM AUTHOR]

Impacts of climate change vary from region to region. The 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) mentions that drier areas will be affected by more droughts while the rainfall regime, in general, will become 'rougher'. In West Africa, specifically the area below the Sahel, the climate change signal may be more subtle. Anecdotal evidence from farmers suggests that the onset of rainy season has been shifting forward in time over the past two generations. Recently, detailed atmospheric modelling over the region shows that in the near future too, the onset of rainy season will shift to later periods in the year, roughly from April towards May. The end of rainy season as well as the total amount of rainfall will remain more or less fixed. This implies that adaptation strategies should be twofold. The first part of a comprehensive adaptation strategy would be a continuation of the efforts to produce faster growing rainfed crop cultivars, mainly corn and sorghum. The second part would consist of increased water storage during the wet season for use during dry season. [ABSTRACT FROM AUTHOR]

In semiarid regions, thousands of small reservoirs provide the rural population with water, but their storage volumes and hydrological impact are largely unknown. This paper analyzes the suitability of weather-independent radar satellite images for monitoring small reservoir surfaces. The surface areas of three reservoirs were extracted from 21 of 22 ENVISAT Advanced Synthetic Aperture Radar scenes, acquired bimonthly from June 2005 to August 2006. The reservoir surface areas were determined with a quasi-manual classification approach, as stringent classification rules often failed due to the spatial and temporal variability of the backscatter from the water. The land—water contrast is critical for the detection of water bodies. Additionally, wind has a significant impact on the classification results and affects the water surface and the backscattered radar signal (Bragg scattering) above a wind speed threshold of 2.6 m · s-1. The analysis of 15 months of wind speed data shows that, on 96% of the days, wind speeds were below the Bragg scattering criterion at the time of night time acquisitions, as opposed to 50% during the morning acquisition time. Night time acquisitions are strongly advisable over day time acquisitions due to lower wind interference. Over the year, radar images are most affected by wind during the onset of the rainy season (May and June). We conclude that radar and optical systems are complimentary. Radar is suitable during the rainy season but is affected by wind and lack of vegetation context during the dry season. [ABSTRACT FROM AUTHOR]

Abstract: Granier type sap flow gauges were used to estimate canopy transpiration from a 7-year-old sweet orange (Citrus sinensis L. Osbeck) orchard in Ghana, West Africa. The aim of the study was to use sap flow based transpiration estimates in modelling the stomatal control of water transport under rain-fed and subhumid tropical conditions. Canopy conductance (g c) of the sweet orange was calculated by inverting the Penman–Monteith equation. Both multiple linear regression and a Jarvis-type model, based on a set of environmental control functions, have been used to simulate half-hourly citrus canopy conductance. Both methods could adequately predict bulk stomatal conductance of the orchard and were suitable for use in the Penman–Monteith equation to estimate transpiration rates. In both models, the vapour pressure deficit was the dominant regulator of canopy transpiration as it explained about 80% of the variations in canopy conductance. A simple envelop function of canopy conductance as a function of the solar radiation and vapour pressure deficit was equally suitable for g c prediction. However, the Jarvis formulation provided the best estimation of conductance compared to other models. Validation with separate data sets confirmed the good performance of these models to investigate the response of citrus to changing environmental conditions. [Copyright &y& Elsevier]

Based on the views of a number of stakeholders involved in the development of small reservoir systems in the Upper East Region of Ghana in West Africa, this paper examines the importance of understanding the stakeholders whom the international development community wants to include in its participatory approaches. The paper also aims to show that terms such as ‘participation’, ‘participatory approach’ and ‘participatory planning’ are often used in project proposals, but that in reality the extent to which stakeholders are actually able to participate in projects is limited. This limitation is often due to a lack of understanding by the project organization of the interests and views of the stakeholders, which are then not incorporated in the project process. A stakeholder analysis could provide more insight in the interests, goals and views of all stakeholders involved in a project, as well as in the differences between the stakeholders. In the development of water resources, the long-term sustainability of a project's work is dependent on the manner in which relevant (often local) stakeholders continue the process after the official time of the project has ended. Thus, since the project is dependent on the involvement of relevant stakeholders, the formulation of adequate and appropriate forms of stakeholder engagement that will ensure information exchange and participation is essential. However, as the case study shows, such analyses were not always carried out, thus leading to a number of problems with project implementation and also with transplantation from one region, district or community to another. [ABSTRACT FROM AUTHOR]

Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets. [ABSTRACT FROM AUTHOR]

Abstract: During the last 25 years there has been a great interest in deriving aquifer characteristics from outflow data. This analysis has been mainly based of the drainage of a horizontal aquifer after sudden drawdown, using the Boussinesq approximation. Following the general approach of Brutsaert and Lopez [Brutsaert W, Lopez, JP. Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. Water Resour Res 1998;34(2):233–40], it was determined that for this geometry the aquifer behavior could be characterized by dQ/dt ∝ Q 3 for small t and by dQ/dt ∝ Q 3/2 for large t. It was remarked that dQ/dt ∝ Q for large t is often observed. In practice, it is also difficult to determine if dQ/dt ∝ Q 3 for small t because this behavior can only be observed over a very short period. Here, we present a similar analysis of aquifer behavior based on the more fundamental Laplace solution for penetrated aquifers. It has been shown that also when the drain does not fully penetrate the aquifer, the solution still produces good results [Szilagyi, J. Sensitivity analysis of aquifer parameter estimations based on the Laplace equation with linearized boundary conditions. Water Resour Res 2003;39(6)]. The Laplace solution quickly shows that dQ/dt ∝ Q for t →∞ and dQ/dt ∝ Q ∞ for t →0, after sudden drawdown. This analysis reconfirms previous findings concerning long-time behavior. More importantly, the analysis shows that the exponent B in dQ/dt ∝ Q B does not have a fixed limited value for short times for the given geometry. Further analysis, however, shows that under certain conditions the relation dQ/dt ∝ Q 3 is retained for 0≪ t &#60;1. Detailed examination of the Laplace solution also shows under which types of recharge dynamics a well-identifiable transition takes place between short- and long-term behavior. As long as such a clear transition exists, the aquifer characterization method proposed earlier by Brutsaert and Lopez [Brutsaert W, Lopez, JP. Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. Water Resour Res 1998;34(2):233–40] can be applied. It is shown that for a sharp pulse input, the Laplace solution gives similar results as presented by Brutsaert and Lopez [Brutsaert W, Lopez, JP. Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. Water Resour Res 1998;34(2):233–40]. For a smooth pulse, the transition becomes unclear. What is “smooth” and “sharp” depends on input and aquifer characteristics, whereby shallow aquifers give clearer transitions than deep aquifers for the same input. The analysis shows that when rain ceases suddenly after the aquifer has come into equilibrium with a steady rain input, a usable transition in the relation between dQ/dt and Q can be found as well. Researchers can use the present analysis to assess whether specific aquifers and recharge events can be used for the previously suggested characterization method. [Copyright &y& Elsevier]

Abstract: Measurements of surface runoff from uniform slopes of different lengths in West Africa have shown that longer slopes tend to have less runoff per unit of length than short slopes. The main reason for this scale effect is that once the rain stops, water on long slopes has more opportunity time to infiltrate than water on short slopes. A validated simple model is put forward that quantifies the scale effects and predicts under which circumstances they can be expected to be most significant. An overview is given of management options that are available to farmers to reduce runoff at the field and slope level. The potential effects of these management options on the hydraulic conductivity, Ksat, and Manning''s roughness coefficient, n, are qualified. The model is subsequently used to calculate the effect of changes in Ksat and n on the runoff from slopes under rainfall conditions found in West Africa. Finally, two design examples are given, namely maximum field lengths and dimensioning of interceptor drains. [Copyright &y& Elsevier]

Low-cost dual-frequency receivers and antennas have created opportunities for a wide range of new applications, in regions and disciplines where traditional GNSS equipment is unaffordable. However, the major drawback of using low-cost antenna equipment is that antenna phase patterns are typically poorly defined. Therefore, the noise in tropospheric zenith delay and coordinate time series is increased and systematic errors may occur. Here, we present a field calibration method that fully relies on low-cost solutions. It does not require costly software, uses low-cost equipment (~500 Euros), requires limited specialist expertise, and takes complex processing steps into the cloud. The application is more than just a relative antenna calibration: it is also a means to assess the quality and performance of the antenna, whether this is at a calibration site or directly in the field. We cover PCV calibrations, important for deformation monitoring, GNSS meteorology and positioning, and the computation of PCOs when the absolute position is of interest. The method is made available as an online web service. The performance of the calibration method is presented for a range of antennas of different quality and price in combination with a low-cost dual-frequency receiver. Carrier phase residuals of the low-cost antennas are reduced by 11–34% on L 1 and 19–39% on L 2 , depending on the antenna type and ground plane used. For the cheapest antenna, when using a circular ground plane, the L 1 residual is reduced from 3.85 mm before to 3.41 mm after calibration, and for L 2 from 5.34 mm to 4.3 mm. The calibration reduces the Median Absolute Deviations (MADs) of the low-cost antennas in the vertical direction using Post Processed Kinematic (PPK) by 20–24%. For the cheapest antenna, the MAD is reduced from 5.6 to 3.8 mm, comparable to a geodetic-grade antenna (3.5 mm MAD). The calibration also has a positive impact on the Precise Point Positioning (PPP) results, delivering more precise results and reducing height biases. [ABSTRACT FROM AUTHOR]

Hutton (2016) argued that computational hydrology can only be a proper science if the hydrological community makes sure that hydrological model studies are executed and presented in a reproducible manner. We replied that to achieve this, hydrologists shouldn't "re-invent the water wheel" but rather use existing technology from other fields (such as containers and ESMValTool) and open interfaces (such as BMI) to do their computational science (Hut, 2017). With this paper and the associated release of the eWaterCycle platform and software package1 we are putting our money where our mouth is and provide the hydrological community with a 'FAIR by design' platform to do our science. eWaterCycle is a platform that separates the experiment done on the model from the model code. In eWaterCycle hydrological models are accessed through a common interface (BMI) in Python and run inside of software containers. In this way all models are accessed in a similar manner facilitating easy switching of models, model comparison and model coupling. Currently the following models are available through eWaterCycle: PCR-GLOBWB 2.0, wflow, Hype, LISFLOOD, TopoFlex HBV, MARRMoT and WALRUS. While these models are written in different programming languages they can all be run and interacted with from the Jupyter notebook environment within eWaterCycle. Furthermore, the pre-processing of input data for these models has been streamlined by making use of ESMValTool. Forcing for the models available in eWaterCycle from well known datasets such as ERA5 can be generated with a single line of code. To illustrate the type of research that eWaterCycle facilitates this manuscript includes five case studies: from a simple 'Hello World' where only a hydrograph is generated to a complex coupling of models in different languages. In this manuscript we stipulate the design choices made in building eWaterCycle and provide all the technical details to understand and work with the platform. For system administrators who want to install eWaterCycle on their infrastructure we offer a separate installation guide. For computational hydologist who want to work with eWaterCycle we also provide a video explaining the platform from a users point of view. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research fully compatible with the principles of Open Science as well as FAIR science.1available on Zenodo: doi.org/10.5281/zenodo.5119389 [ABSTRACT FROM AUTHOR]

We are no longer used to worrying about the number of bytes in a message because we tend to measure bandwidth in mbps. However, large bandwidth or high communication speed inevitably comes with high energy costs. LoRa stands for Long-Range Radio and has been designed to communicate over ranges of up to 20 km line-of sight, or 0.5 to 2 km in more realistic natural settings [1]. Communication takes a very small amount of energy and typical nodes can run for years on a few AA batteries. The frequencies used are 433 MHz & 868 MHz (Europe) and 915 MHz (North America), which are free for reasonable use. The downside is that messages have to be small, typically around 100 bytes, with 51 bytes being the general lower limit. For most commercial LoRa networks, message frequency is about one per hour. Clearly, JSON would not be the best way to format measurement data one wants to send with LoRa.Earlier research shows that the best way to compress hydrological data is by combining disciplinary knowledge about the signal with techniques developed in the realm of information theory [2]. The question (partially) answered here is what the best compression approaches are for different hydrological time series. Compression strategies for series of different environmental variables are presented, such as temperature, relative humidity, intervals between raindrops, and water heights. Different strategies are tried for different variables and heuristic arguments are put forward as a guide towards a general approach. The results, including code examples, will be made available through GitHub.[1] Sanchez-Iborra, Ramon, Jesus Sanchez-Gomez, Juan Ballesta-Viñas, Maria-Dolores Cano, and Antonio F. Skarmeta. "Performance Evaluation of LoRa Considering Scenario Conditions." Sensors 18, no. 3 (2018): 772.[2] Weijs, Steven V., Nick van de Giesen, and Marc B. Parlange. "HydroZIP: How hydrological knowledge can be used to improve compression of hydrological data." Entropy 15, no. 4 (2013): 1289-1310.The work leading to these results has received funding from the European Community's Horizon 2020 Programme (2014-2020) under grant agreement No. 776691 (TWIGA). The opinions expressed in the document are of the authors only and no way reflect the European Commission's opinions. The European Union is not liable for any use that may be made of the information. [ABSTRACT FROM AUTHOR]

The dependency structure between hydrological variables is of critical importance to hydrological modelling and forecasting. When a copula capturing that dependence is fitted to a sample, information on the uncertainty of the fit is needed for subsequent hydrological calculations and reasoning. A new method is proposed to report inferential uncertainty in a copula parameter. The method is based on confidence curves constructed with the use of a pseudo maximum likelihood estimator for the copula parameter. The method was tested on synthetic data and then used as a tool in two hydrological examples. The first examines the probability of major floods in two locations on the Rhine River and its tributaries in the same calendar year. In the second example, rainfall-runoff from a karst region in Tunisia was analysed to determine a confidence interval for the delay between precipitation and runoff. [ABSTRACT FROM AUTHOR]

River regulation by the construction of reservoirs represents one of the greatest challenges to the natural flow regime and ecological health of riverine systems globally. The Danjiangkou (DJK) Reservoir is the largest reservoir on the Hangjiang River and commenced operations in 1967. The reservoir was upgraded in 2012 to provide water resource for the South–North water transfer project through central China. However, the effect of the reservoir operations on the downstream hydrological regime and ecological health of the Hanjiang River following the upgrade (increase in dam height and reservoir capacity) has not been examined thus far. The daily discharge series from four stations along the main stem of the Hanjiang River, including a site upstream, were examined from 1950 to 2017. The study series was divided into three periods based on the difference stages of the reservoir operation: (1) 1950–1966, (2) 1967–2012 and (3) 2013–2017. The nature of hydrological alteration, ecological flow requirement and potential ecological risk during the different periods were investigated. The results clearly indicate that the DJK reservoir has significantly modified the hydrological regime in the middle and downstream section of the Hanjiang River, with most significant modifications recorded immediately downstream of the reservoir. None of the observed 'Range of Variability Approach' hydrological indicators fell within the expected range at Huangjiagang following the increase in reservoir capacity. As a result, the ecological flow requirements could not be guaranteed, and the frequency and intensity of ecodeficit increased. The river ecosystem immediately downstream of the dam was observed to be at high risk of ecosystem degradation during the post-dam periods considered. [ABSTRACT FROM AUTHOR]

Particle filters are non‐Gaussian filters, which means that the assumption that the error distribution of the ensemble should be Gaussian is unnecessary. Like the ensemble Kalman filter, particle filters are based on the Monte Carlo approximation to represent the distribution of model states. It requires a substantial number of particles to approximate the probability density function of states in high‐dimensional models, which is prohibitive for real applications. In order to overcome problems with high dimensionality, localization was applied in an Ensemble‐type data assimilation system. This study combines the localization in LETKF (Local Ensemble Transformation Kalman Filter) with particle filters and proposes a new local particle filter with the model state space correction using Gamma test theory for high‐dimensional models. A series of tests with various parameter settings, including different the numbers of particles, observation intervals, localization scale, inflation factors, and observation operators, were used to evaluate the performance of this new method using a Lorenz model with 40 variables. Besides, the proposed filter was applied in the Lorenz model with 1,000 variables to evaluate its performance in the model with higher dimensions. The results show that this approach can deal with the issue of dimensionality, which otherwise leads to the collapse of the particle filters in high‐dimensional systems. The local particle filter is stable and has considerable potential for complex higher‐dimensional models. Plain Language Summary: Particle filters (PFs) are non‐Gaussian filters, which means that the error distribution does not have to be Gaussian. This is an important advantage over ensemble Kalman filters(EnKF), which does assume a Gaussian distribution. Similar to EnKF, PFs need some particles to represent the distribution of model states. However, in high‐dimensional systems, the need for particles is exceptionally large for standard PFs, which limits PF applications for real‐world problems. To reduce the number of particles need, localization is a possible solution. We propose a new PF combining localization and the Gamma test theory, which can be used for high‐dimensional systems. The performance of the proposed algorithm was tested using a Lorenz model with 40 variables, and a set of experiments was conducted. One more test was used to explore the potential of the proposed PFs in the Lorenz model with 1,000 variables. Results show that this new algorithm is stable in high‐dimensional systems, which makes it potentially useful for more complex geophysical models in the real world. Key Points: The new local particle filters based on the Gamma test theory is proposedThe Gamma test theory is used to account for uncertainty in the process of data assimilationThis algorithm has a better performance in the nonlinear case [ABSTRACT FROM AUTHOR]

In this paper, a methodology is proposed to quantitatively evaluate precipitation products for multiple purposes. Evaluation mainly focuses on rainfall characteristics relevant to hydrological or agricultural applications: spatial distribution pattern, effect of aggregation over time, the capture of small-scale variability and seasonality, detection of dry spells and wet spells, and timing and volume of heavy rainfall events. Verification statistics were modified and metrics were reported for extreme weather performance, such as flood and drought monitoring. The analysis was performed for different rainfall categories, over regions dominated by different weather systems or with different topographical structures. The latest versions of seven commonly available, high-resolution rainfall estimates have been evaluated by the method against daily data from 16 rain gauge stations over Tanzania, during 1998-2006. They were TRMM 3B42, CHIRPS, TAMSAT, CMORPH_RAW, CMORPH_BLD, WFDEI_CRU, and CPCU. All products, except for CMORPH_BLD and CPCU, were poorly correlated to gauge data at daily time scale with correlation coefficients,0.5. Five-day aggregation was the minimum time scale that can be used for the products to reach an accuracy better than monthly-mean of gauge data. Their performance varied across different climatic or topographical regions and different rainfall seasons. Timing of precipitation was inaccurately estimated by all products, particularly for heavy rains, with less than 40% hits. The results of the evaluation procedure allow discrimination between available products and better selection of the product to be used for a specific application, such as crop insurance or flood early warning, under particular climatic conditions. [ABSTRACT FROM AUTHOR]

Abstract Inhabitants and ecosystems in delta areas are becoming increasingly vulnerable to the effects of subsidence, caused by anthropogenic activities. Yangon is a city on the periphery of the Irrawaddy delta in Myanmar where little is known about the true extent of this hazard, while its effects can potentially harm millions of its inhabitants. This research presents the magnitude and extent of the subsidence hazard in Yangon through a Persistent Scatterer Interferometry (PSI) time-series analysis on the Sentinel-1 data archives in the period of December 2015 through April 2017. The PSI analysis revealed four distinct zones of varying sizes where vertical velocity differences over 20 mm/yr were found, locally exceeding 110 mm/yr. The significant subsidence zones are exclusively located in young Alluvium deposits and 95% of velocity differences over 10 mm/yr are found at Quaternary age deposits. The addition of loads, such as buildings, predominantly affect subsidence rates in the first decade after placement. Estimates of groundwater extraction for domestic supply, used by more than 2 million inhabitants, correlate with the township average subsidence rates which shows that most subsidence in Yangon can be explained by groundwater extraction. Current operation of groundwater extraction wells induces an aquifer volume loss of 5.5 million cubic meter per year in the aquifer system of Yangon city. Unless groundwater extractions are mitigated, Yangon will be increasingly vulnerable to infrastructural damages, flooding events, and degrading aquifer quality. Highlights • New subsiding areas discovered in Yangon City • Assessment on influence of groundwater extractions, loads, and geology • Tube well operation by Yangon's city council and private extractions included • Site visits to Yangon City and its stakeholders [ABSTRACT FROM AUTHOR]

West African food systems and rural socio-economics are based on rainfed agriculture, which makes society highly vulnerable to rainfall uncertainty and frequent floods and droughts. Reliable rainfall information is currently missing. There is a sparse and uneven rain gauge distribution and, despite continuous efforts, rainfall satellite products continue to show weak correlations with ground measurements. This paper aims to investigate whether water vapor (WV) observations together with temporal information can complement thermal infrared (TIR) data for satellite rainfall retrieval in a Deep Learning (DL) framework. This is motivated by the fact that water vapor plays a key role in the highly seasonal West African rainfall dynamics. We present a DL model for satellite rainfall detection based on WV and TIR channels of Meteosat Second Generation and temporal information. Results show that the WV inhibition of low-level features enables the depiction of strong convective motions usually related to heavy rainfall. This is especially relevant in areas where convective rainfall is dominant, such as the tropics. Additionally, WV data allow us to detect dry air masses over our study area, that are advected from the Sahara Desert and create discontinuities in precipitation events. The developed DL model shows strong performance in rainfall binary classification, with less false alarms and lower rainfall overdetection (FBias < 2.0 ) than the state-of-the-art Integrated MultisatellitE Retrievals for GPM (IMERG) Final Run. [ABSTRACT FROM AUTHOR]

A 3-D numerical method is developed to investigate the spatial distribution of surface fluxes over heterogeneous surfaces in (semi-)arid regions. Quantifying the effects of changes in the momentum, thermal and moisture roughness lengths on the airflow and fluxes in the ABL is important for water resources management and local climate studies. The governing equations and turbulence models are modified to include the effects of atmospheric stability conditions on the airflow. The turbulent airflow in ABL is simulated based on the Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach to understand the air flow over the non-homogeneous surfaces from dry land through the water surface and vice versa. The model can be used to study airflow in neutral and non-neutral ABL over complex and non-homogeneous surfaces. The model results were used to investigate the flow parameters and (heat) flux variations over small water surfaces considering its surrounding conditions. [ABSTRACT FROM AUTHOR]

The three-dimensional (3-D) modelling of water systems involving double-diffusive processes is challenging due to the large computation times required to solve the flow and transport of constituents. In 3-D systems that approach axisymmetry around a central location, computation times can be reduced by applying a 2-D axisymmetric model set-up. This article applies the Reynolds-averaged Navier-Stokes equations described in cylindrical coordinates and integrates them to guarantee mass and momentum conservation. The discretized equations are presented in a way that a Cartesian finite-volume model can be easily extended to the developed framework, which is demonstrated by the implementation into a non-hydrostatic free-surface flow model. This model employs temperature- and salinity-dependent densities, molecular diffusivities, and kinematic viscosity. One quantitative case study, based on an analytical solution derived for the radial expansion of a dense water layer, and two qualitative case studies demonstrate a good behaviour of the model for seepage inflows with contrasting salinities and temperatures. Four case studies with respect to doublediffusive processes in a stratified water body demonstrate that turbulent flows are not yet correctly modelled near the interfaces and that an advanced turbulence model is required. [ABSTRACT FROM AUTHOR]

To promote the advancement of novel observation techniques that may lead to new sources of information to help better understand the hydrological cycle, the International Association of Hydrological Sciences (IAHS) established the Measurements and Observations in the XXI century (MOXXI) Working Group in July 2013. The group comprises a growing community of tech-enthusiastic hydrologists that design and develop their own sensing systems, adopt a multi-disciplinary perspective in tackling complex observations, often use low-cost equipment intended for other applications to build innovative sensors, or perform opportunistic measurements. This paper states the objectives of the group and reviews major advances carried out by MOXXI members toward the advancement of hydrological sciences. Challenges and opportunities are outlined to provide strategic guidance for advancement of measurement, and thus discovery. [ABSTRACT FROM AUTHOR]

In this study, a framework for simulating the flow field and heat transfer processes in small shallow inland water bodies has been developed. As the dynamics and thermal structure of these water bodies are crucial in studying the quality of stored water , and in assessing the heat fluxes from their surfaces as well, the heat transfer and temperature simulations were modeled. The proposed model is able to simulate the full 3-D water flow and heat transfer in the water body by applying complex and time varying boundary conditions. In this model, the continuity, momentum and temperature equations together with the turbulence equations, which comprise the buoyancy effect, have been solved. This model is built on the Reynolds Averaged Navier Stokes (RANS) equations with the widely used Boussinesq approach to solve the turbulence issues of the flow field. Micrometeorological data were obtained from an Automatic Weather Station (AWS) installed on the site and combined with field bathymetric measurements for the model. In the framework developed, a simple, applicable and generalizable approach is proposed for preparing the geometry of small shallow water bodies using coarsely measured bathymetry. All parts of the framework are based on open-source tools, which is essential for developing countries. [ABSTRACT FROM AUTHOR]

Atmospheric stability conditions over the water surface can affect the evaporative and convective heat fluxes from the water surface. Atmospheric instability occurred 72.5% of the time and resulted in 44.7 and 89.2% increases in the average and maximum estimated evaporation, respectively, when compared to the neutral condition for a small shallow lake (Binaba) in Ghana. The proposed approach is based on the bulk-aerodynamic transfer method and the Monin-Obukhov similarity theory (MOST) using standard meteorological parameters measured over the surrounding land. For water surface temperature, a crucial parameter in heat flux estimation from water surfaces, an applicable method is proposed. This method was used to compute heat fluxes and compare them with observed heat fluxes. The heat flux model was validated using sensible heat fluxes measured with a 3-D sonic anemometer. The results show that an unstable atmospheric condition has a significant effect in enhancing evaporation alongside the sensible heat flux from water surfaces. [ABSTRACT FROM AUTHOR]

The three-dimensional (3-D) modelling of water systems involving double-diffusive processes is challenging due to the large computation times required to solve the flow and transport of constituents. In systems that approach axisymmetry around a central location, computation times can be reduced by applying a quasi 3-D axisymmetric model setup. This article applies the Navier-Stokes equations described in cylindrical coordinates, and integrates them to guarantee mass and momentum conservation. The discretized equations are presented in a way that a Cartesian finite volume model can be easily extended to this quasi 3-D framework, which is demonstrated by the implementation into a non-hydrostatic free-surface flow model. This model employs temperature and salinity dependent densities, molecular diffusivities, and kinematic viscosity. Four qualitative case studies demonstrate a good behaviour with respect to expected density and diffusivity driven flow and stratification in shallow water bodies. A fifth case study involves a new validation method that quantifies the radial expansion of a dense water layer developing from a central inflow at the bottom of a shallow water body. [ABSTRACT FROM AUTHOR]

In this study a numerical groundwater reactive transport model of a shallow groundwater aquifer contaminated with volatile organic compounds is developed. In addition to advective–dispersive transport, the model includes contaminant release from source areas, natural attenuation, abiotic degradation by a permeable reactive barrier at the site, and dilution by infiltrating rain. Aquifer heterogeneity is parameterized using pilot points for hydraulic conductivity, specific yield and groundwater recharge. A methodology is developed and applied to estimate the large number of parameters from the limited data at the field site (groundwater levels, groundwater concentrations of multiple chemical species, point-scale measurements of soil hydraulic conductivity, and lab-scale derived information on chemical and biochemical reactions). The proposed methodology relies on pilot point parameterization of hydraulic parameters and groundwater recharge, a regularization procedure to reconcile the large number of spatially distributed model parameters with the limited field data, a step-wise approach for integrating the different data sets into the model, and high performance computing. The methodology was proven to be effective in reproducing multiple contaminant plumes and in reducing the prior parameter uncertainty of hydraulic conductivity and groundwater recharge. Our results further indicate that contaminant transport predictions are strongly affected by the choice of the groundwater recharge model and flow parameters should be identified using both head and concentration measurements. [ABSTRACT FROM AUTHOR]

This paper presents a score that can be used for evaluating probabilistic forecasts of multicategory events. The score is a reinterpretation of the logarithmic score or ignorance score, now formulated as the relative entropy or Kullback-Leibler divergence of the forecast distribution from the observation distribution. Using the information-theoretical concepts of entropy and relative entropy, a decomposition into three components is presented, analogous to the classic decomposition of the Brier score. The information-theoretical twins of the components uncertainty, resolution, and reliability provide diagnostic information about the quality of forecasts. The overall score measures the information conveyed by the forecast. As was shown recently, information theory provides a sound framework for forecast verification. The new decomposition, which has proven to be very useful for the Brier score and is widely used, can help acceptance of the logarithmic score in meteorology. [ABSTRACT FROM AUTHOR]

Current global satellite scatterometer-based soil moisture retrieval algorithms do not take soil characteristics into account. In this paper, the characteristic time length of the soil water index has been calibrated for ten sampling frequencies and for different soil conductivity associated with 12 soil texture classes. The calibration experiment was independently performed from satellite observations. The reference soil moisture data set was created with a 1-D water-flow model and by making use of precipitation measurements. The soil water index was simulated by applying the algorithm to the modeled soil moisture of the upper few centimeters. The resulting optimized characteristic time lengths T increase with longer sampling periods. For instance, a T of 7 days was found for sandy soil when a sampling period of 1 day was applied, whereas an optimized T-value of 18 days was found for a sampling period of 10 days. A maximum rmse improvement of 0.5% vol. can be expected when using the calibrated T-values instead of T = 20. The soil water index and the differentiated T-values were applied to European Remote Sensing (ERS) satellite scatterometer data and were validated against in situ soil moisture measurements. The results obtained using calibrated T-values and T = 20 did not differ (r = 0.39, rmse = 5.4% vol.) and can be explained by the averaged sampling period of 4-5 days. The soil water index obtained with current operational microwave sensors [Advanced Wind Scatterometer (ASCAT) and Advanced Microwave Scanning Radiometer-Earth Observation System] and future sensors (Soil Moisture and Ocean Salinity and Soil Moisture Active Passive) should benefit from soil texture differentiation, as they can record on a daily basis either individually or synergistically using several sensors. The proposed differentiated characteristic time length enables the continuation of the soil water index of sensors with varying sampling periods (e.g., ERS-ASCAT). [ABSTRACT FROM AUTHOR]

Abstract: Long-term historical records of rainfall (P), runoff (Q) and other climatic factors were used to investigate hydrological variability and trends in the Volta River Basin over the period 1901–2002. Potential (E p) and actual evaporation (E), rainfall variability index (δ), Budyko’s aridity index (I A), evaporation ratio (C E ) and runoff ratio (C Q ) were estimated from the available hydroclimatological records. Mann-Kendall trend analysis and non-parametric Sen’s slope estimates were performed on the respective time series variables to detect monotonic trend direction and magnitude of change over time. Rainfall variability index showed that 1968 was the wettest year (δ =+1.75) while 1983 was the driest (δ =−3.03), with the last three decades being drier than any other comparable period in the hydrological history of the Volta. An increase of 0.2mm/yr2 (P <0.05) was observed in E p for the 1901–1969 sub-series while an increased of 1.8mm/yr2 (P <0.01) was recorded since 1970. Rainfall increased at the rate of 0.7mm/yr2 or 49mm/yr between 1901 and 1969, whereas a decrease of 0.2mm/yr2 (6mm/yr) was estimated for 1970–2002 sub-series. Runoff increased significantly at the rate of 0.8mm/yr (23mm/yr) since 1970. Runoff before dam construction was higher (87.5mm/yr) and more varied (CV=41.5%) than the post-dam period with value of 73.5mm/yr (CV=23.9%). A 10% relative decrease in P resulted in a 16% decrease in Q between 1936 and 1998. Since 1970, all the months showed increasing runoff trends with significant slopes (P <0.05) in 9 out of the 12 months. Possible causes, such as climate change and land cover change, on the detected changes in hydroclimatology are briefly discussed. [Copyright &y& Elsevier]

A new type of rainfall sensor (the intervalometer), which counts the arrival of raindrops at a piezo electric element, is implemented during the Tanzanian monsoon season alongside tipping bucket rain gauges and an impact disdrometer. The aim is to test the validity of the Poisson hypothesis underlying the estimation of rainfall rates using an experimentally determined raindrop size distribution parameterisation based on 's exponential one. These parameterisations are defined independently of the scale of observation and therefore implicitly assume that rainfall is a homogeneous Poisson process. The results show that 28.3 % of the total intervalometer observed rainfall patches can reasonably be considered Poisson distributed and that the main reasons for Poisson deviations of the remaining 71.7 % are non-compliance with the stationarity criterion (45.9 %), the presence of correlations between drop counts (7.0 %), particularly at higher arrival rates (ρa>500 m-2s-1), and failing a χ2 goodness-of-fit test for a Poisson distribution (17.7 %). Our results show that whilst the Poisson hypothesis is likely not strictly true for rainfall that contributes most to the total rainfall amount, it is quite useful in practice and may hold under certain rainfall conditions. The parameterisation that uses an experimentally determined power law relation between N0 and rainfall rate results in the best estimates of rainfall amount compared to co-located tipping bucket measurements. Despite the non-compliance with the Poisson hypothesis, estimates of total rainfall amount over the entire observational period derived from disdrometer drop counts are within 4 % of co-located tipping bucket measurements. Intervalometer estimates of total rainfall amount overestimate the co-located tipping bucket measurement by 12 %. The intervalometer principle shows potential for use as a rainfall measurement instrument. [ABSTRACT FROM AUTHOR]

The Food-Energy-Water (FEW) nexus for urban sustainability needs to be analyzed via an integrative rather than a sectoral or silo approach, reflecting the ongoing transition from separate infrastructure systems to an integrated social-ecological-infrastructure system. As technology hubs can provide food, energy, water resources via decentralized and/or centralized facilities, there is an acute need to optimize FEW infrastructures by considering cost-benefit-risk tradeoffs with respect to multiple sustainability indicators. This paper identifies, categorizes, and analyzes global trends with respect to contemporary FEW technology metrics that highlights the possible optimal integration of a broad spectrum of technology hubs for possible cost-benefit-risk tradeoffs. The challenges related to multiscale and multiagent modeling processes for the simulation of urban FEW systems were discussed with respect to the aspects of scaling-up, optimization process, and risk assessment. Our review reveals that this field is growing at a rapid pace and the previous selection of analytical methodologies, nexus criteria, and sustainability indicators largely depended on individual FEW nexus conditions disparately, and full-scale cost-benefit-risk tradeoffs were very rare. Therefore, the potential full-scale technology integration in three ongoing cases of urban FEW systems in Miami (the United States), Marseille (France), and Amsterdam (the Netherlands) were demonstrated in due purpose finally. [ABSTRACT FROM AUTHOR]

The Food-Energy-Water (FEW) nexus for urban sustainability needs to be analyzed via an integrative rather than a sectoral or silo approach, reflecting the ongoing transition from separate infrastructure systems to an integrated social-ecological-infrastructure system. As technology hubs can provide food, energy, water resources via decentralized and/or centralized facilities, there is an acute need to optimize FEW infrastructures by considering cost-benefit-risk tradeoffs with respect to multiple sustainability indicators. This paper identifies, categorizes, and analyzes global trends with respect to contemporary FEW technology metrics that highlights the possible optimal integration of a broad spectrum of technology hubs for possible cost-benefit-risk tradeoffs. The challenges related to multiscale and multiagent modeling processes for the simulation of urban FEW systems were discussed with respect to the aspects of scaling-up, optimization process, and risk assessment. Our review reveals that this field is growing at a rapid pace and the previous selection of analytical methodologies, nexus criteria, and sustainability indicators largely depended on individual FEW nexus conditions disparately, and full-scale cost-benefit-risk tradeoffs were very rare. Therefore, the potential full-scale technology integration in three ongoing cases of urban FEW systems in Miami (the United States), Marseille (France), and Amsterdam (the Netherlands) were demonstrated in due purpose finally. [ABSTRACT FROM AUTHOR]

Irrigated agriculture contributes 40% of total global food production. In the US High Plains, which produces more than 50 million tons per year of grain, as much as 90% of irrigation originates from groundwater resources, including the Ogallala aquifer. In parts of the High Plains, groundwater resources are being depleted so rapidly that they are considered nonrenewable, compromising food security. When groundwater becomes scarce, groundwater withdrawals peak, causing a subsequent peak in crop production. Previous descriptions of finite natural resource depletion have utilized the Hubbert curve. By coupling the dynamics of groundwater pumping, recharge, and crop production, Hubbert-like curves emerge, responding to the linked variations in groundwater pumping and grain production. On a state level, this approach predicted when groundwater withdrawal and grain production peaked and the lag between them. The lags increased with the adoption of efficient irrigation practices and higher recharge rates. Results indicate that, in Texas, withdrawals peaked in 1966, followed by a peak in grain production 9 y later. After better irrigation technologies were adopted, the lag increased to 15 y from 1997 to 2012. In Kansas, where these technologies were employed concurrently with the rise of irrigated grain production, this lag was predicted to be 24 y starting in 1994. In Nebraska, grain production is projected to continue rising through 2050 because of high recharge rates. While Texas and Nebraska had equal irrigated output in 1975, by 2050, it is projected that Nebraska will have almost 10 times the groundwater-based production of Texas. [ABSTRACT FROM AUTHOR]

Near-surface wind speed is typically only measured by point observations. The actively heated fiber-optic (AHFO) technique, however, has the potential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scale processes. Before AHFO can be widely used, its performance needs to be tested in a range of settings. In this work, experimental results on this novel observational wind-probing technique are presented. We utilized a controlled wind tunnel setup to assess both the accuracy and the precision of AHFO under a range of operational conditions (wind speed, angles of attack and temperature difference). The technique allows for wind speed characterization with a spatial resolution of 0.3 m on a 1 s timescale. The flow in the wind tunnel was varied in a controlled manner such that the mean wind ranged between 1 and 17 ms-1. The AHFO measurements are compared to sonic anemometer measurements and show a high coefficient of determination (0.92–0.96) for all individual angles, after correcting the AHFO measurements for the angle of attack. Both the precision and accuracy of the AHFO measurements were also greater than 95 % for all conditions. We conclude that AHFO has the potential to measure wind speed, and we present a method to help choose the heating settings of AHFO. AHFO allows for the characterization of spatially varying fields of mean wind. In the future, the technique could potentially be combined with conventional distributed temperature sensing (DTS) for sensible heat flux estimation in micrometeorological and hydrological applications. [ABSTRACT FROM AUTHOR]

The recent release of consumer-grade dual-frequency receivers sparked scientific interest into use of these cost-efficient devices for high precision positioning and tropospheric delay estimations. Previous analyses with low-cost single-frequency receivers showed promising results for the estimation of Zenith Tropospheric Delays (ZTDs). However, their application is limited by the need to account for the ionospheric delay. In this paper we investigate the potential of a low-cost dual-frequency receiver (U-blox ZED-F9P) in combination with a range of different quality antennas. We show that the receiver itself is very well capable of achieving high-quality ZTD estimations. The limiting factor is the quality of the receiving antenna. To improve the applicability of mass-market antennas, a relative antenna calibration is performed, and new absolute Antenna Exchange Format (ANTEX) entries are created using a geodetic antenna as base. The performance of ZTD estimation with the tested antennas is evaluated, with and without antenna Phase Center Variation (PCV) corrections, using Precise Point Positioning (PPP). Without applying PCVs for the low-cost antennas, the Root Mean Square Errors (RMSE) of the estimated ZTDs are between 15 mm and 24 mm. Using the newly generated PCVs, the RMSE is reduced significantly to about 4 mm, a level that is excellent for meteorological applications. The standard U-blox ANN-MB-00 patch antenna, with a circular ground plane, after correcting the phase pattern yields comparable results (0.47 mm bias and 4.02 mm RMSE) to those from geodetic quality antennas, providing an all-round low-cost solution. The relative antenna calibration method presented in this paper opens the way for wide-spread application of low-cost receiver and antennas. [ABSTRACT FROM AUTHOR]

Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc. [ABSTRACT FROM AUTHOR]

The accuracy of surface meteorological measurements is vital to derive accurate Global Positioning System (GPS) Precipitable Water Vapour (PWV) data. However, in absence of surface meteorological data, data from Numerical Weather Prediction Models (NWP) are used. The accuracy of these models varies depending on the model, region, season and other climatic conditions. In this study, GPS data for derivation of PWV is collected from 13 geodetic permanent stations for the years 2013 to 2016. Five out of 13 GPS stations are equipped with meteorological sensors. The interpolated European Centre for Medium-Range Weather Forecasts (ECMWF) 5th Re-Analysis (ERA5) dataset at these locations is first validated using the meteorological data from these sensors. The assessment shows that the average root mean square errors (RMSE) of surface pressure and temperature values are about 0.72 hPa and 1.04 K respectively. PWV determined also requires information on the weighted mean temperature ( T m ); the T m at the 13 GPS stations was also evaluated using three methods: the temperature and humidity profiles from ERA5 (ERA5 T m ), as well as the T m derived from Bevis and Yao T m - T s relationships. The T m derived from ERA5 was used as a reference to assess the errors of the Bevis and Yao T m . The comparisons show that the average RMSE values of T m derived from the two methods are 2.05 K and 2.02 K respectively. The GPS PWVs calculated using the ERA5 interpolated data (GPS ERA5 PWV) were compared to GPS PWV calculated using the sensor meteorological data (GPS MET PWV) at the 5 stations. The GPS ERA5 PWV values were used as the reference. The RMSE values of the two PWV datasets are in the range of 0.19 mm to 0.90 mm with overall average value of 0.44 mm. Also the computed ERA5 PWV data are compared to GPS ERA5 PWV at the 13 stations. ERA5 PWV values were used as the reference and the RMS errors of the two PWV values are in the range 1.35 mm to 2.25 mm with the overall average value of 1.66 mm. Regarding the seasonal variations, the stations between latitudes 4 ° S and 4 ° N and latitudes 12 ° S to 4 ° S have the highest PWV values in spring and summer while the lowest values occur in summer and winter respectively. [ABSTRACT FROM AUTHOR]