Suitability of North American Regional Reanalysis (NARR) output for hydrologic modelling and analysis in mountainous terrain

Meteorological observations at high elevations in mountainous regions are often lacking. One opportunity to fill this data gap is through the use of downscaled output from weather reanalysis models. In this study, we tested the accuracy of downscaled output from the North American Regional Reanalysis (NARR) against high‐elevation surface observations at four ridgetop locations in the southern Coast Mountains of British Columbia, Canada. NARR model output was downscaled to the surface observation locations through three‐dimensional interpolation for air temperature, vapour pressure and wind speed and two‐dimensional interpolation for radiation variables. Accuracy was tested at both the 3‐hourly and daily time scales. Air temperature displayed a high level of agreement, especially at the daily scale, with root mean square error (RMSE) values ranging from 0.98 to 1.21 °C across all sites. Vapour pressure downscaling accuracy was also quite high (RMSE of 0.06 to 0.11 hPa) but displayed some site specific bias. Although NARR overestimated wind speed, there were moderate to strong linear relations (r² from 0.38 to 0.84 for daily means), suggesting that the NARR output could be used as an index and bias‐corrected. NARR output reproduced the seasonal cycle for incoming short‐wave radiation, with Nash–Sutcliffe model efficiencies ranging from 0.78 to 0.87, but accuracy suffered on days with cloud cover, resulting in a positive bias and RMSE ranged from 42 to 46 Wm^{? 2}. Although fewer data were available, incoming long‐wave radiation from NARR had an RMSE of 19 Wm^{? 2} and outperformed common methods for estimating incoming long‐wave radiation. NARR air temperature showed potential to assist in hydrologic analysis and modelling during an atmospheric river storm event, which are characterized by warm and wet air masses with atypical vertical temperature gradients. The incorporation of a synthetic NARR air temperature station to better represent the higher freezing levels resulted in increased predicted peak flows, which better match the observed run‐off during the event. Copyright © 2016 John Wiley & Sons, Ltd.     

Semi-empirical prediction method for monthly precipitation prediction based on environmental factors and comparison with stochastic and machine learning models

ABSTRACT

Precipitation prediction is central in hydrology and water resources planning and management. This paper introduces a semi-empirical predictive model to predict monthly precipitation and compares its predictive skill with those of machine learning (ML) methods. The stochastic method presented herein estimates monthly precipitation with one-step-ahead prediction properties. The ML predictive skill of the algorithms is evaluated by predicting monthly precipitation relying on the statistical association between precipitation and environmental and topographic factors. The semi-empirical predictive model features non-negative matrix factorization (NMF) for investigating the influence of multiple predictor variables on precipitation. The semi-empirical predictive model’s parameters are optimized with the hybrid genetic algorithm (GA) and Levenberg-Marquardt algorithm (LM), or GALMA, yielding a validated model with high predictive skill. The methodologies are illustrated with data from Hubei Province, China, which comprise 27 meteorological station datasets from 1988–2017. The empirical results provide valuable insights for developing semi-empirical rainfall prediction models.     

A technique for the determination of areal average rainfall / Une méthode pour la détermination de précipitation moyenne pour une zone donnée

Abstract

A method was developed for allocating an area likely to be shared by a raingauge station. Average areal precipitation was found by weighting the rainfall at the gauging station in terms of the product of distances enclosing it or radiating from it. The method was applied to two real and two hypothetical basins and the results were compared with those obtained by existing techniques.     

Simulating streamflow in the Upper Halda Basin of southeastern Bangladesh using SWAT model

ABSTRACT

Most catchments in tropical regions are ungauged and data deficient, complicating the simulation of water quantity and quality. Yet, developing and testing hydrological models in data-poor regions is vital to support water management. Here, we used the Soil and Water Assessment Tool (SWAT) to predict stream runoff in Halda Basin in Bangladesh. While the calibrated model’s performance was satisfactory (R² = 0.80, NSE = 0.71), the model was unable to track the extreme low flow peaks due to the temporal and spatial variability of rainfall which may not be fully captured by using data from one rainfall gauging station. Groundwater delay time, baseflow alpha factor and curve number were the most sensitive parameters influencing model performance. This study improves understanding of the key processes of a catchment in a data-poor, monsoon driven, small river basin and could serve as a baseline for scenario modelling for future water management and policy framework.     

The nature of rainfall in the main drainage sub-basins of Uganda

Abstract

A study of rainfall trends and temporal variations within seven sub-basins of Uganda spanning from 1940 to 2009 has been made. Rainfall climatologies are constructed from observational data, using 36 station records which reflect hydroclimatic conditions. Long-term changes in rainfall characteristics were determined by non-parametric tests (Mann-Kendall and Sen’s T tests), coefficient of variation (CV), precipitation concentration index and drought severity index. Magnitude of change was estimated by applying Sen’s estimator of slope. Decadal variability of rainfall with marked seasonal cycles is evident. Temporal variability of drought patterns is detected. Variations in annual rainfall are low with no significant trends observed in the main drainage sub-basins. Significant trends occur in October, November, December and January. A noticeable decrease in the annual total rainfall was observed mostly in northwestern and southwestern sub-basins. Rainfall trend in the second normal of June–July–August (JJA) was decreasing in all the main drainage sub-basins.

Editor Z.W. Kundzewicz; Associate editor S. Yue

Citation Nsubuga, F.W.N., Botai, O.J., Olwoch, J.M., Rautenbach, C.J.deW., Bevis, Y., and Adetunji, A.O., 2014. The nature of rainfall in the main drainage sub-basins of Uganda. Hydrological Sciences Journal, 59 (2), 278–299.     

Study of Dongting Lake area variation and its influence on water level using MODIS data / Etude de la variation de la surface du Lac Dongting et de son influence sur le niveau d’eau,grâce à des données MODIS

Abstract

Abstract MODerate-resolution Imaging Spectroradiometer (MODIS) is a new generation remote sensing (RS) sensor and its applications in hydrology and water resources have attracted much attention. To overcome the problems of slow response in flood disaster monitoring based on traditional RS techniques in China, the Flood Disaster Monitoring and Assessing System (FDMAS), based on MODIS and a Geographic Information System (GIS), was designed and applied to Dongting Lake, Hunan Province, China. The storage curve of Dongting Lake for 1995 was obtained using 1:10 000 topographic map data and then a relationship between water level at the Chenglingji hydrological station and lake area was derived. A new relationship between water level and lake area was obtained by processing MODIS images of Dongting Lake from April 2002 to April 2003 and the influence of lake area variation on water level was analysed with the 1996 flood data. It was found that the water level reduction reached 0.64 m for the 1996 flood if the original lake area curve was replaced with the area curve of 2002. This illustrates that the flood water level has been considerably reduced as a result of the increased area of Dongting Lake since the Chinese Central Government’s ?return land to lake? policy took effect in 1998.     

Vertical zonality of the water cycle and the impact of land-use change on runoff in the Qingshui River Basin of Wutai Mountain,China

ABSTRACT

Hydrological processes in hilly watersheds are significantly affected by variations in elevation; however, the hydrological functions of different vertical vegetation belts, have rarely been reported. The distributed hydrological model WEP-L (Water and Energy transfer Process in Large river basins) was applied to analyse vertical variations in the hydrological processes of Qingshui River basin (QRB), Wutai Mountain (altitude: 3058 m a.s.l.), China. The results show that the highest ratio of evapotranspiration to precipitation occurs at 1800 m a.s.l. Below 1800 m, evapotranspiration is mainly controlled by precipitation, and in regions above1800 m it is controlled by energy. The runoff coefficients for different vertical vegetation belts may be ranked as follows: farmland > grassland > subalpine meadow > evergreen coniferous shrub forest > deciduous broad-leaved forest. Grassland is the largest runoff production area, contributing approximately 39.10% to the annual water yield of the QRB. The runoff from forested land decreased to a greater extent than the grassland runoff. Increasing forest cover may increase evapotranspiration and reduce runoff. These results are important, not only for further understanding of the hydrological mechanisms in this basin, but also for implementing the sustainable management of water resources and ecosystems in other mountainous regions.     

Delineation of precipitation regions in two Canadian study areas: the role of the temporal resolution of the precipitation data

The identification of homogeneous precipitation regions has value in many water resources engineering applications (infrastructure planning, design, operations; climate forecasting, modelling). The objective of this paper is to assess the sensitivity of precipitation regions to the temporal resolution (monthly, seasonal, annual and the annual maximum series) of the data. The presented method uses the fuzzy c-means clustering algorithm to partition climate sites into statistically homogeneous precipitation regions. The regions are validated using an approach based on L-moment statistics. The method is conducted in two climatically different study areas in western and eastern Canada. There does not appear to be a relationship between the spatial distributions of the regions formed using different temporal resolutions of the precipitation data. It is recommended to delineate precipitation regions that are specific to the task at hand, and to select a temporal resolution that is consistent with the final application of the regional precipitation dataset.

EDITOR A. Castellarin; ASSOCIATE EDITOR T. Kjeldsen     

Precipitation patterns and associated hydrological extremes in the Yangtze River basin,China, using TRMM/PR data and EOF analysis

Abstract

A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.     

Pluie ou neige? Dispositif de mesures pluviographiques dans les Andes de Bolivie et interprétation des enregistrements/Rainfall or snowfall? Device for measuring the precipitation phase in the Bolivian Andes and analysis of the records

Abstract

Abstract The knowledge of the precipitation phase, solid or liquid, is important in high mountains, in order to use models of water and energy balances. During an experiment led in the Bolivian Andes, a complete weather station was installed at an altitude close to 4800 m, including two raingauge recorders, the first one with added antifreeze and oil, based on weight measurement, and the other one with tipping buckets. This device allowed a realistic partition of the liquid and solid phases in this region of tropical mountains, where the observed snow pack at the ground level is strongly influenced by the extremely high solar radiation and where the snow cover is ephemeral. The automation of the ?raingauges? method, compared with several other classical methods, shows satisfactory results.     

Exploring socio-hydrological determinants of crop yield in under-performing irrigation schemes: pathways for sustainable intensification

ABSTRACT

Understanding the human–water–food–climate nexus is central to achieving sustainable intensification (SI) in agriculture. This research uses a socio-hydrological approach to understand the underpinning for implementing SI in the Gezira Irrigation Scheme, Sudan, by integrating vegetation indices derived from remote sensing, ancillary, gridded soil and precipitation data, supplemented by interviews with 393 farmers. The productivity gap was estimated as the difference between the potential and actual productivities. Based upon data on farmers’ socio-economic status and field practices, a regression tree model was built to determine the factors that control the sorghum yield. The model revealed that the financial status of farmers and access to water are the most influential factors on sorghum yield. A conceptual framework that elucidates SI and its bi-directional feedback to the environment, society and the economy is proposed. Implementing SI in the scheme has implications on water and food security in Sudan and beyond its borders.     

Exploring socio-hydrological determinants of crop yield in under-performing irrigation schemes: pathways for sustainable intensification

ABSTRACT

Understanding the human–water–food–climate nexus is central to achieving sustainable intensification (SI) in agriculture. This research uses a socio-hydrological approach to understand the underpinning for implementing SI in the Gezira Irrigation Scheme, Sudan, by integrating vegetation indices derived from remote sensing, ancillary, gridded soil and precipitation data, supplemented by interviews with 393 farmers. The productivity gap was estimated as the difference between the potential and actual productivities. Based upon data on farmers’ socio-economic status and field practices, a regression tree model was built to determine the factors that control the sorghum yield. The model revealed that the financial status of farmers and access to water are the most influential factors on sorghum yield. A conceptual framework that elucidates SI and its bi-directional feedback to the environment, society and the economy is proposed. Implementing SI in the scheme has implications on water and food security in Sudan and beyond its borders.     

Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records

Abstract

New mathematical programming models are proposed, developed and evaluated in this study for estimating missing precipitation data. These models use nonlinear and mixed integer nonlinear mathematical programming (MINLP) formulations with binary variables. They overcome the limitations associated with spatial interpolation methods relevant to the arbitrary selection of weighting parameters, the number of control points within a neighbourhood, and the size of the neighbourhood itself. The formulations are solved using genetic algorithms. Daily precipitation data obtained from 15 rain gauging stations in a temperate climatic region are used to test and derive conclusions about the efficacy of these methods. The developed methods are compared with some naïve approaches, multiple linear regression, nonlinear least-square optimization, kriging, and global and local trend surface and thin-plate spline models. The results suggest that the proposed new mathematical programming formulations are superior to those obtained from all the other spatial interpolation methods tested in this study.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Teegavarapu, R.S.V., 2012. Spatial interpolation using nonlinear mathematical programming models for estimation of missing precipitation records. Hydrological Sciences Journal, 57 (3), 383–406.     

Long-range forecasts of River Po discharges based on predictable solar activity and a fuzzy neural network model / Prévisions à long terme des débits du Fleuve Pô basées sur l’activité solaire prévisible et sur un modèle de réseau de neurones flou

Abstract

Abstract Is it possible to make seasonal and interannual forecasts of hydrological variables if one cannot predict next week’s rainfall? Contrary to common view, some scientists support the hypothesis that variations in mean global temperature and precipitation are controlled more by external forcing (solar variability and volcanic eruptions) than by increasing atmospheric concentration of greenhouse gases. Temperature and precipitation are connected with special phases of the 11-year sunspot cycle, which coincide with significant accumulation of energetic solar eruptions. Because of the possibility of identifying years with many solar eruptions, the attractive prospect emerges of the long-term hydrological forecasting based on cycles of solar activity. Starting from this assumption, an expert system was built based on a fuzzy neural network model for seasonal and interannual forecasting of the Po River discharge. It was found that indices of solar activity and of global circulation are sufficient to yield useful forecasts of hydrological variables.     

Groundwater storage change detection from in situ and GRACE-based estimates in major river basins across India

ABSTRACT

India has been the subject of many recent groundwater studies due to the rapid depletion of groundwater in large parts of the country. However, few if any of these studies have examined groundwater storage conditions in all of India’s river basins individually. Herein we assess groundwater storage changes in all 22 of India’s major river basins using in situ data from 3420 observation locations for the period 2003–2014. One-month and 12-month standardized precipitation index measures (SPI-1 and SPI-12) indicate fluctuations in the long-term pattern. The Ganges and Brahmaputra basins experienced long-term decreasing trends in precipitation in both 1961–2014 and the study period, 2003–2014. Indeterminate or increasing precipitation trends occurred in other basins. Satellite-based and in situ groundwater storage time series exhibited similar patterns, with increases in most of the basins. However, diminishing groundwater storage (at rates of >0.4 km³/year) was revealed in the Ganges-Brahmaputra River Basin based on in situ observations, which is particularly important due to its agricultural productivity.     

A 200-year precipitation index for the central English Lake District / Un indice de précipitation de 200 ans pour la Région des Lacs en Angleterre

Abstract

Abstract The geographical context and hydroclimatology of the English Lake District means that the region is an important monitor of changes to nationally significant environmental assets. Using monthly rainfall series for sites in and around the central Lake District, a continuous ~200-year precipitation index was constructed for a representative station close to Grasmere. The bridged series shows a significant decline in summer rainfall since the 1960s, offset by increases in winter and spring that are strongly linked to North Atlantic forcing. Over longer time periods, the index exhibits several notable dry (1850s, 1880s, 1890s, 1930s, 1970s) and wet (1820s, 1870s, 1920s, 1940s, 1990s) decades. These patterns are strongly reflected by reservoir inflow series and by indicators of the biological status of the region’s freshwater lakes. It is argued that long-term climate indices will become increasingly important as managers seek to evaluate recent and project environmental changes within the context of long-term natural variability.     

Epidemiological analysis of malaria and its relationships with hydrological variables in four municipalities of the State of Amazonas,Brazil

Abstract

This work comprises a spatial, temporal and statistical analysis of the epidemiology of malaria occurrence in four municipalities of the State of Amazonas, Brazil: Coari, Codajás, Manacapuru and Manaus, for the period 2003–2009. The number of malaria cases, precipitation, water level and temperature data were analysed in this study. The strength of the relationship between these hydrological/meteorological variables and the occurrence of malaria was determined by employing the Spearman rank correlation coefficient. Seasonal peaks of malaria were registered, on average, about 1–2 months before the annual maximum temperature and after the river’s seasonal high-water level. The phenomenon called repiquete (notable variations in the water level) was observed during periods of between 9 and 56 days. The results showed a statistically significant correlation between malaria, temperature, precipitation and water level. Temperature influenced malaria occurrence the least, while rainfall was the most important factor, especially in the municipality of Coari. Water level had an important influence on the records of malarial occurrence in the municipality of Manacapuru.

Editor Z.W. Kundzewicz

Citation Wolfarth, B.R., Filizola, N., Tadei, W.P., and Durieux, L., 2013. Epidemiological analysis of malaria and its relationships with hydrological variables in four municipalities of the State of Amazonas, Brazil. Hydrological Sciences Journal, 58 (7), 1495–1504.     

Evaluation of satellite-based rainfall products for hydrological modelling in Morocco

ABSTRACT

Several satellite-based precipitation estimates are becoming available at a global scale, providing new possibilities for water resources modelling, particularly in data-sparse regions and developing countries. This work provides a first validation of five different satellite-based precipitation products (TRMM-3B42 v6 and v7, RFE 2.0, PERSIANN-CDR, CMORPH1.0 version 0.x) in the 1785 km² Makhazine catchment (Morocco). Precipitation products are first compared against ground observations. Ten raingauges and four different interpolation methods (inverse distance, nearest neighbour, ordinary kriging and residual kriging with altitude) were used to compute a set of interpolated precipitation reference fields. Second, a parsimonious conceptual hydrological model is considered, with a simulation approach based on the random generation of model parameters drawn from existing parameter set libraries, to compare the different precipitation inputs. The results indicate that (1) all four interpolation methods, except the nearest neighbour approach, give similar and valid precipitation estimates at the catchment scale; (2) among the different satellite-based precipitation estimates verified, the TRMM-3B42 v7 product is the closest to observed precipitation, and (3) despite poor performance at the daily time step when used in the hydrological model, TRMM-3B42 v7 estimates are found adequate to reproduce monthly dynamics of discharge in the catchment. The results provide valuable perspectives for water resources modelling of data-scarce catchments with satellite-based rainfall data in this region.

Editor M.C. Acreman; Associate editor N. Verhoest     

Precipitation in tropical America and the associated sources of moisture: a short review

Abstract

Understanding of the relationship between precipitation and the associated sources of moisture is essential to the improvement of our comprehension of the global water cycle. The observation of precipitation is one of the major challenges in the study of climate, as is the proper assignment of the sources of moisture that account for that precipitation. A stark contrast in the amounts of available information on precipitation may be seen in the cases of Central America and the northern part of South America. The main areas of precipitation in tropical America are described, and the moisture sources for these areas are identified by means of a Lagrangian approach presented with an example application. A strong relationship exists between the identified sources of moisture and the distribution of precipitation in the locations in question. The Caribbean Sea and the tropical Atlantic are highlighted as the main sources of moisture for the regions of highest precipitation in tropical America. Regional low-level winds play a major role in transport of moisture from the adjacent oceanic regions.

Editor Z.W. Kundzewicz

Citation Durán-Quesada, A.M., Reboita, M. and Gimeno, L., 2012. Precipitation in tropical America and the associated sources of moisture: a short review. Hydrological Sciences Journal, 57 (4), 612–624.