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1.
Seasonal forecasting can be highly valuable for water resources management. Hydrological models (either lumped conceptual rainfall-runoff models or physically based distributed models) can be used to simulate streamflows and update catchment conditions (e.g. soil moisture status) using rainfall records and other catchment data. However, in order to use any hydrological model for skillful seasonal forecasting, rainfall forecast at relevant spatial and/or temporal scales is required. Together with downscaling, general circulation models are probably the only tools for making such seasonal predictions. The Predictive Ocean Atmosphere Model for Australia (POAMA) is a state-of-the-art seasonal climate forecast system developed by the Australian Bureau of Meteorology. Based on the preliminary assessment on the performance of existing statistical downscaling methods used in Australia, this paper is devoted to develop an analogue downscaling method by modifying the Euclidian distance in the selection of similar weather pattern. Such a modification consists of multivariate Box–Cox transformation and then standardization to make the resulted POAMA and observed climate pattern more similar. For the predictors used in Timbal and Fernadez (CAWCR Technical Report No. 004, 2008), we also considered whether the POAMA precipitation provides useful information in the analogue method. Using the high quality station data in the Murray Darling Basin of Australia, we found that the modified analogue method has potential to improve the seasonal precipitation forecast using POAMA outputs. Finally, we found that in the analogue method, the precipitation from POAMA should not be used in the calculation of similarity. The findings would then help to improve the seasonal forecast of streamflows in Australia.  相似文献   

2.
Understanding precipitation variations from various aspects is important for the assessment of drought risk and the utilization of water resources. The precipitation concentration index (PCI) and the concentration index (CI) were used to investigate/quantify the heterogeneity of the monthly and daily rainfall in Qinghai province that is part of northwestern China, respectively. The precipitation concentration in Qinghai shows a significant irregularity of the monthly rainfall distribution and highly homogeneous distribution of the daily rainfall. It is found that PCI and CI show negative trends at most stations. Meanwhile, the spatial and temporal variation of nine dry spell (DS) indices are analyzed. From the spatial perspective, drought in the northwestern area is much severer than that in other areas of Qinghai. According to the results of temporal analysis by using the Mann–Kendall test, the number of very long DSs, maximum length of DS, mean length of DSs, and the total dry days of extreme DS all decrease. All these results verify that the warm dry climatic pattern in Qinghai can be changed into the warm wet climatic pattern.  相似文献   

3.
Soil erosion by water is one of the main environmental concerns in the drought‐prone Eastern Africa region. Understanding factors such as rainfall and erosivity is therefore of utmost importance for soil erosion risk assessment and soil and water conservation planning. In this study, we evaluated the spatial distribution and temporal trends of rainfall and erosivity for the Eastern Africa region during the period 1981–2016. The precipitation concentration index, seasonality index, and modified Fournier index have been analysed using 5 × 5‐km resolution multisource rainfall product (Climate Hazards Group InfraRed Precipitation with Stations). The mean annual rainfall of the region was 810 mm ranging from less than 300 mm in the lowland areas to over 1,200 mm in the highlands being influenced by orography of the Eastern Africa region. The precipitation concentration index and seasonality index revealed a spatial pattern of rainfall seasonality dependent on latitude, with a more pronounced seasonality as we go far from the equator. The modified Fournier index showed high spatial variability with about 55% of the region subject to high to very high rainfall erosivity. The mean annual R‐factor in the study region was calculated at 3,246 ± 1,895 MJ mm ha?1 h?1 yr?1, implying a potentially high water erosion risk in the region. Moreover, both increasing and decreasing trends of annual rainfall and erosivity were observed but spatial variability of these trends was high. This study offers useful information for better soil erosion prediction as well as can support policy development to achieve sustainable regional environmental planning and management of soil and water resources.  相似文献   

4.
Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann–Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity.  相似文献   

5.
Abstract

Characterization of the seasonal and inter-annual spatial and temporal variability of rainfall in a changing climate is vital to assess climate-induced changes and suggest adequate future water resources management strategies. Trends in annual, seasonal and maximum 30-day extreme rainfall over Ethiopia are investigated using 0.5° latitude?×?0.5° longitude gridded monthly precipitation data. The spatial coherence of annual rainfall among contiguous rainfall grid points is also assessed for possible spatial similarity across the country. The correlation between temporally coinciding North Atlantic Multidecadal Oscillation (AMO) index and annual rainfall variability is examined to understand the underlying coherence. In total 381 precipitation grid points covering the whole of Ethiopia with five decades (1951–2000) of precipitation data are analysed using the Mann-Kendall test and Moran spatial autocorrelation method. Summer (July–September) seasonal and annual rainfall data exhibit significant decreasing trends in northern, northwestern and western parts of the country, whereas a few grid points in eastern areas show increasing annual rainfall trends. Most other parts of the country exhibit statistically insignificant trends. Regions with high annual and seasonal rainfall distribution exhibit high temporal and spatial correlation indices. Finally, the country is sub-divided into four zones based on annual rainfall similarity. The association of the AMO index with annual rainfall is modestly good for northern and northeastern parts of the country; however, it is weak over the southern region.

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

Citation Wagesho, N., Goel, N.K., and Jain, M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal, 58 (2), 354–373.  相似文献   

6.
Regional characteristics of extreme precipitation indices (EPI) of precipitation magnitude, intensity and persistence were analyzed based on a daily rainfall dataset of 135 stations during the period of 1961–2010 in the Yangtze River basin, China. The spatial distribution of temporal trends of the selected indices was regionally mapped and investigated by using non-parametric test method. Future projections of EPI changes derived from the output of general circulation model (HadCM3) under the SRES A2 and B2 emission scenarios were downscaled and analyzed. The results show that: (a) there is not a general significant increasing or decreasing trend in EPI for the Yangtze River basin based on historical recorded data; (b) the automated statistical downscaling method-based precipitation captures some spatial distribution of the EPI and the bias correction can improve the simulation results; (c) a mixed pattern of positive and negative changes is observed in most of the nine indices under both scenarios in the first half of twenty-first century, and they increase continuously in the second half of twenty-first century; and (d) the concurrent increase in the heavy rain and drought indices indicates the possibility of the sudden change from drought to water logging in the lower region of Yangtze River basin.  相似文献   

7.
Isotope data of precipitation and groundwater in parts of the Voltaian Basin in Northern Ghana were used to explain the groundwater recharge regime in the area. Groundwater recharge is an important parameter in the development of a decision support system for the management and efficient utilization of groundwater resources in the area. It is therefore important to establish the processes and sources of groundwater recharge. δ18O and δ2H data for local precipitation suggest enrichment relative to the Global Meteoric Water Line (GMWL) and indicate that precipitation takes place at a relative humidity less than 100%. The groundwater data plot on an evaporation line with a slope of 5, suggesting a high degree of evaporative enrichment of the precipitation in the process of vertical infiltration and percolation through the unsaturated zone into the saturated zone. This finding is consistent with the observation of high evapotranspiration rates in the area and ties in with the fact that significant clay fraction in the unsaturated zone limits vertical percolation and thus exposes the percolating rainwater to the effects of high temperatures and low humidities resulting in high evapotranspiration rates. Groundwater recharge estimates from the chloride mass balance, CMB, method suggest recharge in the range of 1.8–32% of the annual average precipitation in the form of rainfall. The highest rates are associated with areas where open wells encourage significant amount of groundwater recharge from precipitation in the area. In the northern parts of the study area, groundwater recharge is lower than 12%. The recharge so computed through the application of the CMB methodology takes on a spatial distribution akin to the converse of the spatial pattern of both δ18O and δ2H in the area. As such, the locations of the highest recharge are associated with the most depleted values of the two isotopes. This observation is consistent with the assertion that low vertical hydraulic conductivities slow down vertical percolation of precipitation down to the groundwater water. The percolating precipitation water thus gets enriched in the heavier isotopes through high evapotranspiration rates. At the same time, the amount of water that finally reaches the water table is considerably reduced. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

8.
Despite the importance of mountain ranges as water providers, knowledge of their climate variability is still limited, mostly due to a combination of data scarcity and heterogeneous orography. The tropical Andes share many of the main features of mountain ranges in general, and are subject to several climatic influences that have an effect on rainfall variability. Although studies have addressed the large-scale variation, the basin scale has received little attention. Thus, the purpose of this study was to obtain a better understanding of rainfall variability in the tropical Andes at the basin scal, utilizing the Paute River basin of southern Ecuador as a case study. Analysis of 23 rainfall stations revealed a high spatial variability in terms of: (i) large variations of mean annual precipitation in the range 660–3400 mm; (ii) the presence of a non-monotonic relation between annual precipitation and elevation; and (iii) the existence of four, sometimes contrasting, rainfall regimes. Data from seven stations for the period 1964–1998 was used to study seasonality and trends in annual, seasonal and monthly precipitation. Seasonality is less pronounced at higher elevations, confirming that in the páramo region, the main water source for Andean basins, rainfall is well distributed year round. Additionally, during the period of record, no station has experienced extreme concentrations of annual rainfall during the wet season, which supports the concept of mountains as reliable water providers. Although no regional or basin-wide trends are found for annual precipitation, positive (negative) trends during the wet (dry) season found at four stations raises the likelihood of both water shortages and the risk of precipitation-triggered disasters. The study demonstrates how variable the precipitation patterns of the Andean mountain range are, and illustrates the need for improved monitoring. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

9.
We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy. Through the embedding into a hierarchical Bayesian estimation framework, we can use the integrated nested Laplace approximation methodology to make inference and obtain the posterior estimates of spatially distributed covariate and random effects. Several mapping units are useful to partition a given study area in landslide prediction studies. These units hierarchically subdivide the geographic space from the highest grid-based resolution to the stronger morphodynamic-oriented slope units. Here we integrate both mapping units into a single hierarchical model, by treating the landslide triggering locations as a random point pattern. This approach diverges fundamentally from the unanimously used presence–absence structure for areal units since we focus on modeling the expected landslide count jointly within the two mapping units. Predicting this landslide intensity provides more detailed and complete information as compared to the classically used susceptibility mapping approach based on relative probabilities. To illustrate the model’s versatility, we compute absolute probability maps of landslide occurrences and check their predictive power over space. While the landslide community typically produces spatial predictive models for landslides only in the sense that covariates are spatially distributed, no actual spatial dependence has been explicitly integrated so far. Our novel approach features a spatial latent effect defined at the slope unit level, allowing us to assess the spatial influence that remains unexplained by the covariates in the model. For rainfall-induced landslides in regions where the raingauge network is not sufficient to capture the spatial distribution of the triggering precipitation event, this latent effect provides valuable imaging support on the unobserved rainfall pattern.  相似文献   

10.
Abstract

The study of precipitation trends is critically important for a country like India whose food security and economy are dependent on the timely availability of water. In this work, monthly, seasonal and annual trends of rainfall have been studied using monthly data series of 135 years (1871–2005) for 30 sub-divisions (sub-regions) in India. Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three (Haryana, Punjab and Coastal Karnataka), this trend was statistically significant. Similarly, only one sub-division (Chattisgarh) indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall. In India, the monsoon months of June to September account for more than 80% of the annual rainfall. During June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall. In August, the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite. The majority of sub-divisions showed very little change in rainfall in non-monsoon months. The five main regions of India showed no significant trend in annual, seasonal and monthly rainfall in most of the months. For the whole of India, no significant trend was detected for annual, seasonal, or monthly rainfall. Annual and monsoon rainfall decreased, while pre-monsoon, post-monsoon and winter rainfall increased at the national scale. Rainfall in June, July and September decreased, whereas in August it increased, at the national scale.

Citation Kumar, V., Jain, S. K. & Singh, Y. (2010) Analysis of long-term rainfall trends in India. Hydrol. Sci. J. 55(4), 484–496.  相似文献   

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