Dew Point Time Series Forecasting at the North Dakota

Hydrological time series forecasting is one of the hot topics in the domain of statistical hydrology. Providing accurate forecasting can contribute to diverse applications for catchment sustainability and management. Dew point temperature (Tdew) is one of the complex hydrological processes that highly essential to be quantified accurately for several catchment activities such as crops, agriculture, and others. In this study, three types of models’ recursive strategy, direct strategy, and DirRec which is the combination of recursive and direct strategies were adopted to obtain h-steps ahead predictions of Tdew. Ten years monthly scale dataset of Tdew at two meteorological stations (Beach and Cavalier) located at the North Dakota, USA, were used for the modeling development. The performance of the considered models was compared with two benchmark models: autoregressive moving average (ARIMA) and exponential smoothing (ETS). Modeling results indicated that, compared with the benchmark models, the proposed methods gave good results for the multi-ahead forecasting. For instance, for Cavalier station, the root mean squared prediction errors obtained from the proposed and benchmark methods when the forecast horizon is 12 are as follows: recursive strategy (RMSPE = 3.731) direct strategy (RMSPE = 3.385), DirRec (RMSPE = 3.141), ARIMA (RMSPE = 12.957), and ETS (RMSPE = 27.479).

Avaliação de metodologias de transferência de vazões de referência em bacias hidrográficas: sua aplicação na bacia do rio Japaratuba - Sergipe - Brasil

Para avaliar a disponibilidade de água e definir as áreas de inundação nas bacias hidrográficas, é necessário considerar a vazão mínima, média e máxima, denominadas de vazões de referência, e isto requer dados observados de vazão, que são bem escassos em bacias brasileiras, principalmente as pequenas e médias bacias. Para superar esta falta, utiliza-se dados de bacias contribuintes com comportamento hidrológico similar, que são transferidos por meio de operações matemáticas, utilizando variáveis físicas e climáticas. Tais procedimentos, geralmente, são mal avaliados quanto à sua precisão. Assim, objetivou avaliar a acurácia da estimação de cinco vazões de referência em quatro estações de medição dos dois principais afluentes do rio Japaratuba (Sergipe, Brasil), os rios Japaratuba-Mirim e Siriri. Os resultados mostraram diferentes comportamentos para as duas sub-bacia, quer seja pelas variáveis influentes, quer seja pelos efeitos antrópicos como a mudança no uso do solo que precisam ser melhor avaliados. Para a bacia do rio Japaratuba-Mirim a transferência de vazões mínimas e médias deve ser realizada considerando-se o produto área x precipitação média anual e para as vazões máximas deve-se considerar o comprimento do rio até a seção. Para a bacia do Siriri, os melhores resultados de transferência de vazões médias e máximas foram obtidos com o produto "área x precipitação média anual” e a variável "precipitação média anual" gerou um erro menor para as vazões mínimas. Assessing the reference flow transfer methodologies in watersheds: their application at Japaratuba River Basin – Sergipe State – BrazilA B S T R A C TIn order to evaluate the water availability and define the flood areas in the river basins, it is necessary to consider minimum, medium and maximum discharge, called reference flows requiring records on flow data, quite scarce in Brazilian river basin, mainly those of small and medium scale. To overcome this gap, data from nearby basins with similar hydrological behavior are used, based on mathematical operations involving physical and climatic variables of the contributing basins. However, these procedures are poorly evaluated for their accuracy. Thus, this study aimed to evaluate the accuracy of the estimation of five reference flows through the transfer of information, using physical and climatic variables in four gage stations of the main tributaries of the Japaratuba river basin (Japaratuba-Mirim and Siriri river) - Sergipe State, Brazil. The results showed different behaviors for the two sub-basins as for either by influential variables or by anthropic effects such as land use and land cover changes that need to be better evaluated. The flow transfer to the subbasin of the Japaratuba-Mirim river should be performed considering the product "Area x Mean annual rainfall" for minimum and medium flows. For maximum flows the "Length" of the basin should be considered. For the Siriri river basin, the "Mean annual rainfall" variable generated a smaller error in the minimum flows and the product "Area x Mean annual rainfall” led to better results for medium and maximum flows.Keywords: Water resource management; statistical hydrology; geographic information systems.

Spatial variability of precipitation extremes over Italy using a fine-resolution gridded product

<p>Analysis of extreme precipitation events has been the cornerstone of statistical hydrology and plays a crucial role in planning and designing hydraulic structures. Extreme value theory offers a solid theoretical basis for using the Generalized Extreme Value (GEV) distribution as a probabilistic model to describe precipitation annual maxima. Several large-scale studies investigate the properties of the GEV distribution in point measurements offering insights on its spatial variability. Yet the sparse station network in most regions, as anticipated, leads to sparse point estimates that may distort the actual spatial patterns of the GEV’s parameters. Here, we use fine-resolution satellite-based gridded product, that is, the CHIRPS v2.0, to investigate the spatial variation of the GEV distribution over Italy. Our results show that the GEV shape parameter forms clear spatial patterns. We use these results to offer robust estimates and create maps for different return periods all over Italy.</p>

A Canadian viewpoint on data, information and uncertainty in the context of prediction in ungauged basins

The quality (i.e. the degree of uncertainty that results from the interpretation and analysis) of information dictates its value for decision making. There has been much progress towards improving information on the water budgets of ungauged basins by improving knowledge, tools and techniques during the Prediction in Ungauged Basins (PUB) initiative. These improvements, at least in Canada, have come through efforts in both hydrological process and statistical hydrology research. This paper is a review of some recent Canadian PUB efforts to use data to generate information and reduce uncertainty about the hydrological regimes of ungauged basins. The focus is on the Canadian context and the problems it presents, but the lessons learned are applicable to other countries with similar challenges. With a large land mass that is relatively poorly gauged, novel approaches have had to be developed to extract the most information from the available data. It can be difficult in Canada to find gauged or research basins sufficiently similar to ungauged sites of interest that contain the data required to force either statistical or deterministic models. Many statistical studies have improved information or at least an understanding of the quality of that information, of ungauged basin streamflow regimes using innovative regression-based approaches and pooled frequency analysis. Hydrological process research has reduced knowledge uncertainty, particularly in regard to cold regions processes, and this situation has led to the development of new algorithms that are reducing predictive uncertainty. There remains much to do. Current progress has created an opportunity to better integrate statistical and deterministic models via data assimilation of regionalization model estimates and those from coupled atmospheric-hydrological models. Aspects of such a modelling system could also provide more robust uncertainty analyses than traditional approaches.