RECONCILING PRECIPITATION WITH RUNOFF: THE ROLE OF UNDERSTATED MEASUREMENT BIASES IN THE MODELLING OF HYDROLOGICAL PROCESSES

    Progetto: Research project

    Description

    Inaccurate precipitation measurements have been recently recognised as the “wilfully neglected Achille’s heel” of hydro-meteorological sciences. Difficulties in achieving accurate measurements arise from various instrumental and environmental sources of systematic biases, resulting in a significant underestimation of the precipitation depth and intensity. The understated extent of the associated biases is largely unknown and varies with various environmental factors, due to the complexity of the controlling processes. Although attempts were made to standardise measurement procedures, this has never been successfully achieved.Without any correction for or, in many cases, any awareness of such measurement errors, there is a grave risk of a breakdown in the understanding of hydro-meteorological processes in a scientific era dominated by modelling, which generally undervalues the principals of precise and accurate measurements. Implications describe an inconvenient truth in hydrological sciences, which transcends a variety of applications of precipitation data in hydrological models, from real-time flood forecasting to water resources management and urban hydrology. The calibration of satellite- and radar-based areal estimates of precipitation and the statistics derived from historic data series are also systematically affected.The extent and implications of inherent instrumental biases and wind-induced undercatch of precipitation measurements in the modelling of hydrological processes at the basin scale is the main focus of this research project. The aim is to quantify the impact of incorrect measurements used as the forcing variable of physically based hydrological models on their typical output variables, including the flood peak and volume, time to peak, baseflow separation and the regression curves. The impact on the simulation of hydrological processes at the basin scale is investigated, such as evapotranspiration, infiltration, interception, etc. The methods used to achieve the project objectives include theoretical analysis, numerical simulation (CFD, distributed hydrological models, interpolation and data integration, statistical analysis) and full-scale experiments performed in the laboratory (wind tunnel) and in real-world experimental basins.The main expected result is to provide scientific evidence of precipitation measurement biases and their impact on hydrological models, by showing the improvement obtained when corrections for instrumental and environmental errors are implemented. To achieve this, other intermediate results will be obtained, e.g. the development of suitable correction curves for the wind-induced undercatch, the improvement of areal rainfall estimates based on the integration of rain gauge, radar and satellite sources, and the development of dedicated statistical tools to improve the assessment of homogeneity in precipitation time series, climatic trends and extreme value statistics.

    Layman's description

    The project aims at quantifying the impact of Precipitation Measurement Biases (PMBs) on the modelling of hydrological processes at the catchment scale. Both local and areal methods for estimating precipitation rates are addressed, as well as instrumental and environmental sources of uncertainty in measurements. Particularly, in this project, the research unit of Palermo University, focus on the impact of PMBs on rainfall products at a high temporal resolution, by studying the propagation of errors into the hydraulic modelling of urban drainage networks. To this aim, the fully monitored Parco d’Orleans urban catchment located in the University Campus of Palermo, Italy is considered. High space/time resolution rainfall and runoff data series are available since 1996. The total drainage area is 12.8 ha with 68% of impervious areas; the drainage network is composed of circular and egg-shaped concrete conduits. The sensitivity of this rapid response system to the accuracy of the rainfall input is studied, with reference to drainage failures and urban flooding issues.For rainfall-runoff transformation in the urban drainage system we use a conceptual rainfall-runoff model for urban catchment, which incorporates, semi-distributed modelling concepts [36]. In this model, the catchment is divided in external sub-catchments connected to the drainage network. Each external sub-catchment is modelled as two separate conceptual linear elements, a reservoir and a channel, one for the pervious part, the other for the impervious part of the drainage area. The drainage network is schematized as a cascade of non-linear cells and the flood routing is simplified in the form of kinematic wave and represented as a flux transfer between adjacent cells. The main expected impact of the project is to foster more accurate precipitation measurements by raising the awareness of the (now greatly understated) relevance of measurement accuracy in hydrological applications having a strong societal impact (floods, water resources, climate trends, etc.). We believe that a sound scientific basis is essential to demonstrate that PMBs of traditional rain gauges are not negligible in currently operational networks and may lead to large errors in the interpretation of precipitation patterns in both space and time. The project will provide such a sound scientific evidence.The interpretation of rainfall patterns, speculations about the nature of the rain field, scaling vs. non-scaling issues, rainfall event modelling and forecasting efforts, everyday engineering applications, etc., are all based on the analysis of rainfall intensity measurements that are recorded at a much lower accuracy than the available technology would actually permit. The homogenization of climate data is also of major importance because the real climatic signal in the original series of meteorological data is often hidden behind non-climatic noise, and thus the conclusions of climatic and hydrological studies are potentially biased.The technological and economic impacts of the project are strong in that our research will demonstrate that the currently operational instruments and data-logger are not sufficiently advanced to guarantee that PMBs are minimised and only the residual noise (random errors) will affect precipitation records. At the same time, specifications and solutions to achieve measurements that are more accurate will be provided so that rain gauge manufacturers will have the opportunity to gain advantages on the market in case they will decide to improve their instruments accordingly.

    Key findings

    Ambiente e cambiamento climatico
    StatoAttivo
    Data di inizio/fine effettiva2/5/172/5/20