Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments

ABSTRACT

Climate patterns, including rainfall prediction, is one of the most complex problems for hydrologist. It is inherited by its natural and stochastic phenomena. In this study, a new approach for rainfall time series forecasting is introduced based on the integration of three stochastic modelling methods, including the seasonal differencing, seasonal standardization and spectral analysis, associated with the genetic algorithm (GA). This approach is specially tailored to eradicate the periodic pattern effects notable on the rainfall time series stationarity behaviour. Two different climates are selected to evaluate the proposed methodology, in tropical and semi-arid regions (Malaysia and Iraq). The results show that the predictive model registered an acceptable result for the forecasting of rainfall for both the investigated regions. The attained determination coefficient (R²) for the investigated stations was approx. 0.91, 0.90 and 0.089 for Mosul, Baghdad and Basrah (Iraq), and 0.80, 0.87 and 0.94 for Selangor, Negeri Sembilan and Johor (Malaysia).     

Analysis of long-term rainfall trends in India

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.     

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.     

Modelling diurnal cycles in point rainfall properties

A hybrid model for point rainfall has been explored to model the diurnal cycles in rainfall properties. The hybrid model is a product of two random processes: an occurrence process and an intensity process. Two occurrence process models, first‐order Markov chain and periodic discrete autoregressive, were compared initially. Fourier series was fitted to the properties of the occurrence and intensity processes of the observed data in order to reduce the number of model parameters. The Bayesian and Akaike information criteria were used to identify the optimum number of harmonics of the Fourier series. Simulation results of the two hybrid models were similar, if not identical, and compared well with the observed. In the average sense, the introduction of diurnal cycles in the model parameters did not improve the reproduction of the observed aggregation properties of the occurrence process. However, the diurnal distributions of the aggregation statistics were significantly improved by increasing the order of the Markov chain model. Also the information criteria tend to favour higher than first‐order Markov chain models. Copyright © 2001 John Wiley & Sons, Ltd.     

Comparative evaluation of statistical tests for time series analysis: application to hydrological time series / Evaluation comparative de tests statistiques pour l'analyse de séries temporelles: application à des séries temporelles hydrologiques

Abstract

Statistical analyses of hydrological time series play a vital role in water resources studies. Twenty-nine statistical tests for detecting time series characteristics were evaluated by applying them to analyse 46 years of annual rainfall, 47 years of 1-day maximum rainfall and consecutive 2-, 3-, 4-, 5- and 6-day maximum rainfalls at Kharagpur, West Bengal, India. The performance of all the tests was evaluated. No severe outliers were found, and both the annual and maximum rainfall series were found to be normally distributed. Based on the known physical parameters affecting the homogeneity, the cumulative deviations and the Bayesian tests were found to be superior to the classical von Neumann test. Similarly, the Tukey test proved excellent among all the multiple comparison tests. These tests indicated that all the seven rainfall series are homogeneous. Two parametric t tests and the non-parametric Mann-Whitney test indicated stationarity in all the rainfall series. Of 12 trend detection tests, nine tests indicated no trends in the rainfall series. The Kendall's Rank Correlation test and the Mann-Kendall test were found equally powerful. Moreover, the Fourier series analysis revealed no apparent periodicities in all the seven rainfall series. The annual rainfall series was found persistent with a time lag of nine years. All the rainfall series were subjected to stochastic analysis by fitting 35 autoregressive moving-average (ARMA) models of different orders. The best-fit models for the original annual rainfall and 1-, 2- and 3-day maximum rainfall series were found to be ARMA(0,4), ARMA(0,2), ARMA(0,2) and ARMA(3,0), respectively. The best-fit model for the logarithmically transformed 4-day maximum rainfall was found to be ARMA(0,2). However, for the inversely transformed 4-, 5- and 6-day maximum rainfall series, ARMA(0,1) was obtained as the best-fit model. It is concluded that proper selection of time series tests and use of several tests is indispensable for making useful and reliable decisions.     

Precipitation trend analysis using discrete wavelet transform at the Langat River Basin,Selangor, Malaysia

The main purpose of this study was to determine the most dominant periodic components that affect the annual and seasonal precipitation trends in each homogenous rainfall region in the Langat River Basin, Malaysia for the period 1982–2011. Performing this research could be essential because in the previous studies on detection of trend in Malaysia, the details of variations of different time scales and the periodic responsible for the observed trends were not investigated. Using discrete wavelet transform (DWT) coupled with Mann–Kendall at the regional scale for the first time particularly in the context of Malaysia is the contribution of this study. In order to form the homogenous rainfall regions, first the total annual and seasonal precipitation in each year was spatialized into 5 km × 5 km grids using the inverse distance weighting method. The obtained precipitation series for the grids were then grouped applying the Ward’s clustering method based on the similarity of precipitation time series. After allocating a cluster number to each grid, the boundary of the regions was formed in ArcGIS software. Following which, in each homogenous region the areal precipitation series were computed by the Thiessen polygon method. The Mann–Kendall (MK) test was used to detect trend and the DWT coupled with the MK test and the sequential MK analysis were then utilized in order to find out the time scale which affected the observed trend in each homogenous region. On annual scale, it was found that D₁ (plus approximation) component in regions Annual Cluster1 (AC1) and AC2 was the periodic mode responsible for trends. On seasonal scale, in regions Northeast monsoon Cluster 1 (NC1), NC3, SC1 and Southwest monsoon Cluster 2 (SC2), D₁ (with approximation), in regions NC4, Inter monsoon 1 Cluster 1 (I1C1), I1C2, Inter monsoon 2 Cluster 1 I2C1 and I2C2, Detail 2 (D₂) (plus approximation) and in region NC2, Detail 3 (D₃) (with approximation added) component were the most influential periodicity for trends.     

THE RHONE GLACIER SURVEYS

Abstract

This paper describes a stochastic rainfall model which has been developed to generate synthetic sequences of hourly rainfalls at a point. The model has been calibrated using data from Farnborough in Hampshire, England. This rainfall data series was divided into wet and dry spells; analysis of the durations of these spells suggests that they may be represented by exponential and generalized Pareto distributions respectively. The total volume of rainfall in wet spells was adequately fitted by a conditional gamma distribution. Random sampling from a beta distribution, defining the average shape of all rainfall profiles, is used in the model to obtain the rainfall profile for a given wet spell. Results obtained from the model compare favourably with observed monthly and annual rainfall totals and with annual maximum frequency distributions of 1, 2, 6, 12, 24 and 48 hours duration at Farnborough. The model has a total of 22 parameters, some of which are specific to winter or summer seasons.     

Drought frequency analysis of annual rainfall series in central and western Sudan

Abstract

Rainfall is the most important water resource in central and western Sudan, a region affected by the recent drought in Africa. A general methodology for studying the annual rainfall process is presented and applied to data from central and western Sudan. It is assumed that certain time series models adequately describe the annual rainfall process in the region. Based on this assumption, the drought frequencies are calculated in the subregions with stationary series. The theory of runs is applied in calculating drought frequencies using a data generation method.     

Trend analysis of water discharge and sediment load during the past three decades of development in the Langat basin,Malaysia

Abstract

In this study, the trends of water discharge and sediment load from three hydrometric stations over the past 25 years of development in the state of Selangor, Peninsular Malaysia, were analysed using the Mann-Kendall and Pettitt tests. Landscape metrics for establishing the relationship between land-use changes and trends of hydrological time series were calculated. The hydrological trends were also studied in terms of rainfall variations and manmade features. The results indicate upward trends in water discharge in the Hulu Langat sub-basin and in sediment load in the Semenyih sub-basin. These increasing trends were mainly caused by rapid changes in land use. Upward trends of hydrological series in the Hulu Langat sub-basin matched its rainfall pattern. In the Lui sub-basin, however, trends of hydrological series, and variations in rainfall and land use were not statistically significant.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Memarian, H., Balasundram, S.K., Talib, J.B., Sood, A.M., and Abbaspour, K.C., 2012. Trend analysis of water discharge and sediment load during the past three decades of development in the Langat basin, Malaysia. Hydrological Sciences Journal, 57 (6), 1207–1222.     

Water balance of Lake Victoria: update to 2000 and climate change modelling to 2100 / Bilan hydrologique du Lac Victoria: mise à jour jusqu’en 2000 et modélisation des impacts du changement climatique jusqu’en 2100

Abstract

Abstract An annual water balance model of Lake Victoria is derived for the period 1925–2000. Regression techniques are used to derive annual inputs to the water balance, based on lake rainfall data, measured and derived inflows and estimated evaporation during the historical period. This approach acknowledges that runoff is a nonlinear function of lake rainfall. A longer inflow series is produced here which is representative of the whole inflow to the lake, rather than just from individual tributaries. The results show a good simulation of annual lake levels and outflows and capture the high lake level in 1997–1998. Climate change scenarios, from a recent global climate model experiment, are applied to the lake rainfall inflow series and evaporation data to estimate future water balances of the lake. The scenarios produce a potential fall in lake levels by the 2030s horizon, and a rise by the 2080s horizon. A discussion of the application of climate change data to this complex hydrological system is presented.     

Inconsistent linear trends in Senegalese rainfall indices from 1950 to 2007

Abstract

Daily precipitation data from 31 Senegalese stations spanning the period from 1950 to 2007 were used to examine the inter-annual variations of seven rainfall indices: the annual mean precipitation (MEAN); the annual standard deviation of daily precipitation (STD); the frequency of wet days (Prcp1); the maximum number of consecutive dry days (CDD); the maximum 3-day rainfall total (R3D); the wet day precipitation intensity (SDII); and the 90th percentile of rain-day precipitation (Prec90p). The indices were spatially averaged over three agro-climatic regions in Senegal. Trends in the time series of the averaged indices were assessed using both visual examination and a modified version of the Mann-Kendall (MM-K) test. Initially negative significant trends in all seven indices suggest gradually drier conditions over the three agro-climatic regions between 1950 and 1980. In contrast, no significant trends, or even positive significant trends, were observed from the mid-1980s to 2007. The MM-K test was applied to all available data (1950–2007) and the period from 1971 to 2000. While several indices were found to have significant trends towards drier conditions for the 1950–2007 period, only PRCP1 showed a positive significant trend for the 1971–2000 period. The MM-K test did not detect a significant trend for the other indices. It was found that the rainfall deficit and therefore drought is no longer intensifying, and that the region may even become wetter. However, the period covered by the observations is still too short to resolve the question of whether there is now a trend towards wetter conditions.

Editor Z.W. Kundzewicz; Associate editor K. Hamed     

Analysis and modelling of rainfall fields at different resolutions in southern Italy

Abstract

The spatial and temporal variability of the scaling properties and correlation structure of a data set of rainfall time series, aggregated over different temporal resolutions, and observed in 70 raingauges across the Basilicata and Calabria regions of southern Italy, is investigated. Two types of random cascade model, namely canonical and microcanonical models, were used for each raingauge and selected season. For both models, different hypotheses concerning dependency of parameters on time scale and rainfall height can be adopted. In particular, a new approach is proposed which consists of several combinations of models with a different scale dependence of parameters for different temporal resolutions. The goal is to improve the modelling of the main features of rainfall time series, especially for cases where the variability of rainfall changes irregularly with temporal aggregation. The results obtained with the new methodology showed good agreement with the observed data, in particular, for the summer months. In fact, during this season, rainfall heights aggregated at fine temporal resolutions (from 5 to 20 min) are more similar (relative to the winter season) to the values cumulated on 1 or 3 h (due to convective phenomena) and, consequently, the process of rainfall breakdown is nearly stationary for a range of finer temporal resolutions.

Editor D. Koutsoyiannis; Associate editor A. Montanari     

The use of the exponent K(q) function to delimit homogeneous regions in regional frequency analysis of extreme annual daily rainfall

The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions (γ_max and K(0)) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimation of the generalized logistic distribution of extreme events using partial L-moments

Abstract

Statistical analysis of extreme events is often carried out to predict large return period events. In this paper, the use of partial L-moments (PL-moments) for estimating hydrological extremes from censored data is compared to that of simple L-moments. Expressions of parameter estimation are derived to fit the generalized logistic (GLO) distribution based on the PL-moments approach. Monte Carlo analysis is used to examine the sampling properties of PL-moments in fitting the GLO distribution to both GLO and non-GLO samples. Finally, both PL-moments and L-moments are used to fit the GLO distribution to 37 annual maximum rainfall series of raingauge station Kampung Lui (3118102) in Selangor, Malaysia, and it is found that analysis of censored rainfall samples of PL-moments would improve the estimation of large return period events.

Editor D. Koutsoyiannis; Associate editor K. Hamed

Citation Zakaria, Z.A., Shabri, A. and Ahmad, U.N., 2012. Estimation of the generalized logistic distribution of extreme events using partial L-moments. Hydrological Sciences Journal, 57 (3), 424–432.     

The contribution of tropical cyclones to rainfall in Mexico

Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country’s water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.     

Runoff characteristics of a glacierized catchment,Garhwal Himalaya,India

Abstract

Discharge characteristics and the role of monsoonal rainfall in the glacierized Dokriani catchment in the Ganga River headwaters, Garhwal Himalaya, India are examined for the summer ablation period of 1994. Monsoonal rainfall over the glacierized area appears to be an important factor controlling the characteristics of the discharge hydrograph. Monsoonal cloud cover reduces the energy input resulting in subdued ice melt. The monsoonal component was separated from the bulk flow hydrograph recorded close to the glacier snout using a mass balance approach: 11.46% of the total discharge of 62.38 x l0⁶ m³ was contributed by the rainfall over the catchment.     

Stochastic modelling of seasonal and yearly rainfalls with low-frequency variability

Stochastic rainfall models are important for many hydrological applications due to their appealing ability to simulate synthetic series that resemble the statistical characteristics of the observed series for a location of interest. However, an important limitation of stochastic rainfall models is their inability to preserve the low-frequency variability of rainfall. Accordingly, this study presents a simple yet efficient stochastic rainfall model for a tropical area that attempts to incorporate seasonal and inter-annual variabilities in simulations. The performance of the proposed stochastic rainfall model, the tropical climate rainfall generator (TCRG), was compared with a stochastic multivariable weather generator (MV-WG) in various aspects. Both models were applied on 17 rainfall stations at the Kelantan River Basin, Malaysia, with tropical climate. The validations were carried out on seasonal (monsoon and inter-monsoon) and annual basis. The third-order Markov chain of the TCRG was found to perform better in simulating the rainfall occurrence and preserving the low-frequency variability of the wet spells. The log-normal distribution of the TCRG was consistently better in modelling the rainfall amounts. Both models tend to underestimate the skewness and kurtosis coefficient of the rainfall. The spectral correction approach adopted in the TCRG successfully preserved the seasonal and inter-annual variabilities of rainfall amounts, whereas the MV-WG tends to underestimate the variability bias of rainfall amounts. Overall, the TCRG performed reasonably well in the Kelantan River Basin, as it can represent the key statistics of rainfall occurrence and amounts successfully, as well as the low-frequency variability.     

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.     

Simulating the impacts of land-use and climate change on water resource availability for a large south Indian catchment

Abstract

A monthly rainfall-runoff model was calibrated for a large tropical catchment in southern India. Various land-use and climatic change scenarios were tested to assess their effects on mean annual runoff and assured water yield at the Bhavanisagar Reservoir in Tamil Nadu, India. The largest increase in runoff (19%) came from converting forest and savanna (the indigenous control scenario) to agriculture. Mean annual runoff decreased by 35% after conversion to commercial forest and 6% after partial conversion to tea plantations. The predicted climate scenarios of reduced dry season rainfall decreased the annual runoff by 5% while enhanced annual rainfall caused a 17% increase in runoff. Even if land-use and climate changes had relatively large effects on runoff, the changes in reservoir yield which can be assured every year, were often less severe. This was probably due to the buffering effect of the reservoir and variation in the mean annual runoff.