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Rainfall is a major requirement for many water resources applications, including food production and security. Understanding the main drivers of rainfall and its variability in semi-arid areas is a key to unlocking the complex rainfall processes influencing the translation of rainfall into runoff. In recent studies, temperature and humidity were found to be among rainfall predictors in Botswana and South African catchments when using complex rainfall models based on the generalized linear models (GLMs). In this study, we explore the use of other less complex models such as artificial neural networks (ANNs), and Multiplicative Autoregressive Integrated Moving Average (MARIMA) (a) to further investigate the association between rainfall and large-scale rainfall predictors in Botswana, and (b) to forecast these predictors to simulate rainfall at shorter future time scales (October–December) for policy applications. The results indicate that ANN yields better estimates of forecasted temperatures and rainfall than MARIMA.Editor D. Koutsoyiannis; Guest editor D. Hughes [ABSTRACT FROM PUBLISHER]

Broken line smoothing is a simple technique for smoothing a broken line fit to observational data and provides a flexible means of interpolation. Here an extension of this technique is proposed, which can be utilized to perform various interpolation tasks, by incorporating, in an objective manner, an explanatory variable available at a considerably denser dataset than the initial main variable. The technique incorporates smoothing terms with adjustable weights, defined by means of the angles formed by the consecutive segments of two broken lines. The mathematical framework and details of the method as well as practical aspects of its application are presented and discussed. Also, examples using both synthesized and real-world (soil water dynamics and hydrological) data are presented to explore and illustrate the methodology.Editor Z.W. Kundzewicz; Associate editor A. Carsteanu [ABSTRACT FROM PUBLISHER]

In a recent development in the literature, a new temporal rainfall model, based on the Bartlett-Lewis clustering mechanism and intended for sub-hourly application, was introduced. That model replaced the rectangular rain cells of the original model with finite Poisson processes of instantaneous pulses, allowing greater variability in rainfall intensity over short intervals. In the present paper, the basic instantaneous pulse model is first extended to allow for randomly varying storm types. A systematic comparison of a number of key model variants, fitted to 5-min rainfall data from Germany, then generates further new insights into the models, leading to the development of an additional model extension, which introduces dependence between rainfall intensity and duration in a simple way. The new model retains the original rectangular cells, previously assumed inappropriate for fine-scale data, obviating the need for the computationally more intensive instantaneous pulse model.Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

A distributed 1D rainfall–runoff model is presented. It consists of the Saint Venant continuity and momentum equations for overland flow and a modified Green-Ampt model for the infiltration on railway embankment steep slopes. The model is applied to adjacent 10-m-wide erosion control experimental plots with different percentages of grass cover. A relationship between the 2-day antecedent rainfall and initial moisture content was established and used to predict the saturated hydraulic conductivity (Ks). Average values of Ks for 0, 50 and 100% grass cover were found to be 0.1, 1.19 and 2.56 mm/h, respectively. For the majority of cases, the model simulated runoff with acceptable accuracy, 68% having Nash-Sutcliffe efficiency (NSE) values above 0.50. The average NSE value varied between 0.60 and 0.80, with 0% grass-covered plots yielding the highest values. As expected, the runoff volume decreased with increasing percentage of grass cover. Citation Sajjan, A.K., Gyasi-Agyei, Y., and Sharma, R.H., 2013. Rainfall–runoff modelling of railway embankment steep slopes. Hydrological Sciences Journal, 58 (5), 1162–1176. Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

According to the Peruvian agricultural ministry, the Pacific watersheds where the great cities and intense farming are located only benefit from 1% of the available freshwater in Peru. Hence a thorough knowledge of the hydrology of this region is of particular importance. In the paper, analysis of this region and of the two other main Peruvian drainages, the Titicaca and Amazonas are reported. Rainfall and runoff data collected by the Peruvian National Service of Meteorology and Hydrology (SENAMHI) and controlled under the Hydrogeodynamics of the Amazon Basin (HyBAm) project is the basis of this basin-scale study that covers the 1969–2004 period. Beyond the strong contrasting rainfall conditions that differentiate the dry coastal basins and the wet eastern lowlands, details are given about in situ runoff and per basin rainfall distribution in these regions, and about their different altitude–rainfall relationships. Rainfall and runoff variability is strong in the coastal basins at seasonal and inter-annual time scales, and related to extreme El Niño events in the Pacific Ocean. However, rainfall and runoff are more regular in the Andes and Amazonas at the inter-annual time scale. Warm sea-surface temperatures in the northern tropical Atlantic tend to produce drought in the southern Andes basins. Moreover, significant trends and change-points are observed in the runoff data of Amazonas basins where rainfall and runoff decrease, especially after the mid-1980s and during the low-stage season. Almost all the coastal basins show some change in minimum runoff during the last 35 years while no change is observed in rainfall. This means that human activity may have changed runoff in this region of Peru, but this hypothesis deserves more study. Editor Z.W. Kundzewicz; Associate editor Š. Blažková Citation Lavado C., W.S., Ronchail, J., Labat, D., Espinoza, J.C. and Guyot, J.L., 2012. Basin-scale analysis of rainfall and runoff in Peru (1969–2004): Pacific, Titicaca and Amazonas watersheds. Hydrological Sciences Journal, 57 (4), 625–642. [ABSTRACT FROM PUBLISHER]

The availability of precipitation records in Uganda has significantly decreased since the 1970s, severely limiting the data available for hydrological modelling. This problem has been addressed in this study by using the generalized linear modelling (GLM) framework to develop stochastic daily rainfall models that have the capability for extending and infilling historic data sets. We have used a relatively sparse raingauge network in the Kyoga basin (in the Upper Nile) to reproduce spatial and temporal patterns of precipitation by fitting occurrence (logistic) and amounts (gamma) models as functions of dominant seasonal, climate and geographical controls. The GLMs were able to reproduce rainfall properties when predefined climatic zones are modelled independently. We were not able to represent the spatial variability of the equatorial climate with one integrated basin scale model, however this is not thought to preclude application to basin scale hydrological modelling. Citation Kigobe, M., McIntyre, N., Wheater, H. & Chandler, R. (2011) Multi-site stochastic modelling of daily rainfall in Uganda. Hydrol. Sci. J. 56(1), 17-33. [ABSTRACT FROM AUTHOR]

Cette etude evalue les consequences de la variabilite climatique sur la maisiculture pluviale dans l'est Ivoirien. Les tests de stationnarite ont mis en evidence des ruptures dans les series pluviometriques a la fin des annees 1960. L'impact de ces decrochages sur les saisons culturales montre que, malgre sa reduction apres les annees 1970, la duree de la premiere saison culturale ne constitue pas un facteur restrictif pour la maisiculture de cycle court. L'evolution des conditions hydriques de la maisiculture et les potentiels de rendements induits ont ete simules sur la base des donnees climatiques et des resultats d'essais de longue duree. Les conditions hydriques ont ete caracterisees en termes de deficit et d'exces d'eau par le modele CROPWAT-FAO de simulation du bilan hydrique. La confrontation des resultats des simulations et des indicateurs descriptifs des tendances de production, montre que l'etat actuel des conditions climatiques n'explique pas la dynamique d'ensemble de la maisiculture dans l'est Ivoirien. Citation Noufe, D., Lidon, B., Mahe, G., Servat, E., Brou, Y. T., Koli, Bi Z., & Chaleard, J.-L. (2011) Variabilite climatique et production de mais en culture pluviale dans l'est Ivoirien. Hydrol. Sci. J. 56(1), 152-167. [ABSTRACT FROM AUTHOR]

Turkish annual precipitation regimes are analysed to provide a large-scale perspective and redefine precipitation regions. Monthly total precipitation data are employed for 107 stations (1963-2002). Precipitation regime shape (seasonality) and magnitude (size) are classified using a novel multivariate methodology. Six shape and five magnitude classes are identified, which exhibit clear spatial structure. A composite (shape and magnitude) regime classification reveals dominant controls on spatial variability of precipitation. Intra-annual timing and magnitude of precipitation is highly variable due to seasonal shifts in Polar and sub-Tropical zones and physiographic factors. Nonetheless, the classification methodology is shown to be a powerful tool that identifies physically-interpretable precipitation regions: (1) coastal regimes for Marmara, coastal Aegean, Mediterranean and Black Sea; (2) transitional regimes in continental Aegean and Southeast Anatolia; and (3) inland regimes across Central and Eastern Anatolia. This research has practical implications for understanding water resources, which are under ever growing pressure in Turkey. Citation Saris, F., Hannah, D. M. & Eastwood, W. J. (2010) Spatial variability of precipitation regimes over Turkey. Hydrol. Sci. J. 55(2), 234-249. [ABSTRACT FROM AUTHOR]