Projection of future rainfall for the North China Plain using two statistical downscaling models and its hydrological implications

This study projected the future rainfall (2046–2065 and 2081–2100) for the North China Plain (NCP) using two stochastic statistical downscaling models, the non-homogeneous hidden Markov model and the generalized linear model for daily climate time series, conditioned by the large-scale atmospheric predictors from six general circulation models for three emission scenarios (A1B, A2 and B1). The results indicated that the annual total rainfall, the extreme daily rainfall and the maximum length of consecutive wet/dry days would decline, while the number of annual rainfall days would slightly increase (correspondingly rainfall intensity would decrease) in the NCP, in comparison with the base period (1961–2010). Moreover, the summer monsoon rainfall, which accounted for 50–75 % of the total annual rainfalls in NCP, was projected to decrease in the latter half of twenty-first century. The spatial patterns of change showed generally north–south gradients with relatively larger magnitude decrease in the northern NCP and less decrease (or even slightly increase) in the southern NCP. This could result in decline of the annual runoff by ?5.5 % (A1B), ?3.3 % (A2) and ?4.1 % (B1) for 2046–2065 and ?5.3 % (A1B), ?4.6 % (A2) and ?1.9 % (B1) decrease for 2081–2100. These rainfall changes, combined with the warming temperature, could lead to drier catchment soil profiles and further reduce runoff potential, would hence provide valuable references for the water availability and related climate change adaption in the NCP.     

A spatial temporal downscaling approach to development of IDF relations for Perth airport region in the context of climate change

ABSTRACT

Downscaling of climate projections is the most adapted method to assess the impacts of climate change at regional and local scales. This study utilized both spatial and temporal downscaling approaches to develop intensity–duration–frequency (IDF) relations for sub-daily rainfall extremes in the Perth airport area. A multiple regression-based statistical downscaling model tool was used for spatial downscaling of daily rainfall using general circulation models (GCMs) (Hadley Centre’s GCM and Canadian Global Climate Model) climate variables. A simple scaling regime was identified for 30 minutes to 24 hours duration of observed annual maximum (AM) rainfall. Then, statistical properties of sub-daily AM rainfall were estimated by scaling an invariant model based on the generalized extreme value distribution. RMSE, Nash-Sutcliffe efficiency coefficient and percentage bias values were estimated to check the accuracy of downscaled sub-daily rainfall. This proved the capability of the proposed approach in developing a linkage between large-scale GCM daily variables and extreme sub-daily rainfall events at a given location. Finally IDF curves were developed for future periods, which show similar extreme rainfall decreasing trends for the 2020s, 2050s and 2080s for both GCMs.

Editor M.C. Acreman; Associate editor S. Kanae     

Frequency analysis of precipitation extremes in Heihe River basin based on generalized Pareto distribution

Precipitation extremes could cause a series of social, environmental and ecological problems. This paper, taking Heihe River basin, the second largest inland river basin in China, as the study area, focused on the frequency analysis of precipitation extremes based on the historical daily precipitation records (1960–2010) at nine stations. Generalized Pareto distribution (GPD) was employed for fitting the peaks over threshold (POT) series, in which Hill plot, percentile method and the average annual occurrence number were used to select the threshold in GPD. Maximum likelihood estimate and L-moment were used to estimate the parameters. The inherent assumptions for POT series were investigated by auto-correlation coefficient, Mann–Kendall test, Spearman’s ρ test, cumulative deviation test and Worsley likelihood ratio test. 10, 20, 50 and 100 year precipitation extremes for Heihe River basin were calculated and analyzed as well. It was found the POT series derived from several methods involved were approximately independent and stationary, and GPD could give a satisfactory fit to the POT series for each station. For the upper and lower reaches, the frequency of precipitation extremes at long return periods (20, 50 year or longer) presented increasing in recent years, and the intensity of the highest precipitation were getting stronger as well. The intensity of the highest precipitation extremes for the lower reach (21 and 35 %) increased higher than those for the upper reach (10 and 11 %). For the middle reach, the frequency of precipitation extremes (over 20 year return level) was not found to be increased. The uneven spatial and temporal distribution of precipitation extremes for the basin especially for the upper and lower reaches were getting more and more serious, which would bring great challenges for the local water allocation and management.     

Climate change and uncertainty assessment over a hydroclimatic transect of Michigan

Predictions of a warmer climate over the Great Lakes region due to global change generally agree on the magnitude of temperature changes, but precipitation projections exhibit dependence on which General Circulation Models and emission scenarios are chosen. To minimize model- and scenario-specific biases, we combined information provided by the 3rd phase of the Coupled Model Intercomparison Project database. Specifically, the results of 12 GCMs for three emission scenarios B1, A1B, and A2 were analyzed for mid- (2046–2065) and end-century (2081–2100) intervals, for six locations of a hydroclimatic transect of Michigan. As a result of Bayesian Weighted Averaging, total annual precipitation averaged over all locations and the three emission scenarios increases by 7 % (mid-)–10 % (end-century), as compared to the control period (1961–1990). The projected changes across seasons are non-uniform and precipitation decreases by 3 % (mid-)–5 % (end-) for the months of August and September are likely. Further, average temperature is very likely to increase by 2.02–2.85 °C by the mid-century and 2.58–4.73 °C by the end-century. Three types of non-additive uncertainty sources due to climate models, anthropogenic forcings, and climate internal variability are addressed. When compared to the emission uncertainty, the relative magnitudes of the uncertainty types for climate model ensemble and internal variability are 149 and 225 % for mean monthly precipitation, and they are respectively 127 and 123 % for mean monthly temperature. A decreasing trend of the frost days and an increasing trend of the growing season length are identified. Also, a significant increase in the magnitude and frequency of heavy rainfall events is projected, with relatively more pronounced changes for heavy hourly rainfall as compared to daily events. Quantifying the inherent natural uncertainty and projecting hourly-based extremes, the study results deliver useful information for water resource stakeholders interested in impacts of climate change on hydro-morphological processes.     

Spatial and temporal variations in rainfall erosivity during 1960–2005 in the Yangtze River basin

Water resources and soil erosion are the most important environmental concerns in the Yangtze River basin, where soil erosion and sediment yield are closely related to rainfall erosivity. The present study explores the spatial and temporal changing patterns of the rainfall erosivity in the Yangtze River basin of China during 1960–2005 at annual, seasonal and monthly scales. The Mann–Kendall test is employed to detect the trends during 1960–2005, and the T test is applied to investigate possible changes between 1991–2005 and 1960–1990. Meanwhile the Rescaled Range Analysis is used for exploring future trend of rainfall erosivity. Moreover the continuous wavelet transform technique is using studying the periodicity of the rainfall erosivity. The results show that: (1) The Yangtze River basin is an area characterized by uneven spatial distribution of rainfall erosivity in China, with the annual average rainfall erosivity range from 131.21 to 16842 MJ mm ha^?1 h^?1. (2) Although the directions of trends in annual rainfall erosivity at most stations are upward, only 22 stations have significant trends at the 90 % confidence level, and these stations are mainly located in the Jinshajiang River basin and Boyang Lake basin. Winter and summer are the seasons showing strong upward trends. For the monthly series, significant increasing trends are mainly found during January, June and July. (3) Generally speaking, the results detected by the T test are quite consistent with those detected by the Mann–Kendall test. (4) The rainfall erosivity of Yangtze River basin during winter and summer will maintain a detected significant increasing trend in the near future, which may bring greater risks to soil erosion. (5) The annual and seasonal erosivity of Yangtze River basin all have one significant periodicity of 2–4 years.     

Temporal and spatial variability of annual and seasonal rainfall over Ethiopia

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.     

Spatio-temporal characteristics of extreme precipitation events during 1951–2011 in Shandong,China and possible connection to the large scale atmospheric circulation

Analyses of the spatio-temporal variability of precipitation extremes defined by eleven extreme precipitation indices in Shandong were conducted by utilizing the methods of linear regression, ensemble empirical mode decomposition (EEMD) and Mann–Kendall test. The results revealed that statistically significant decreasing trends existed for almost all extreme precipitation indices except for the consecutive dry days (CDD) and simple daily intensity index. A periodicity of 10–15 years for precipitation extremes is detected by EEMD analysis. Greatest 5-day total rainfall (RX5day), very wet days (R95p) and annual total wet-day precipitation (PRCPTOT) experienced decreasing trends in the region stretching from the southeast coast to the west, while the spatial distribution of the decreasing trends for other indices was more complicated. Moreover, the frequency of occurrence in precipitation extremes at Changdao station, surrounded by the sea in the northeast region, increased in contrast to surrounding stations. This may suggest a possible effect from the local marine environment on extreme precipitation. In addition, the stations with statistically significant positive trends for CDD were mainly located in mid-west Shandong and along the southeast coast, where the extreme precipitation and total rainfall were, on the contrary, characterized by decreasing trends. These results indicate that drought or severe drought events have become more frequent in those regions. Analysis of large-scale atmospheric circulation changes indicates that a strengthening anticyclonic circulation and increasing geopotential height as well as decreasing strength of monsoonal flow in recent decades may have contributed to the variations in extreme precipitation in Shandong.     

Spatial distribution and temporal trends of mean precipitation and extremes in the arid region,northwest of China,during 1960–2010

On the basis of daily precipitation records at 76 meteorological stations in the arid region, northwest of China, the spatial and temporal distribution of mean precipitation and extremes were analysed during 1960–2010. The Mann–Kendall trend test and linear least square method were utilized to detect monotonic trends and magnitudes in annual and seasonal mean precipitation and extremes. The results obtained indicate that both the mean precipitation and the extremes have increased except in consecutive dry days, which showed the opposite trend. The changes in amplitude of both mean precipitation and extremes show seasonal variability. On an annual basis, the number of rain days (R0.1) has significantly increased. Meanwhile, the precipitation intensity as reflected by simple daily intensity index (SDII), number of heavy precipitation days (R10), very wet days (R95p), max 1‐day precipitation amount (RX1day) and max 5‐day precipitation amount (RX5day) has also significantly increased. This suggests that the precipitation increase in the arid region is due to the increase in both precipitation frequency and intensity. Trends in extremes are very highly correlated with mean trends of precipitation. The spatial correlation between trends in extremes and trends in the mean is stronger for winter (DJF) than for annual and other seasons. The regional annual and seasonal precipitation and extremes are observed the step jump in mean in the late 1980s. Overall, the results of this study are good indicators of local climate change, which will definitely enhance human mitigation to natural hazards caused by precipitation extremes. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparative application of two mathematical models to predict sedimentation in Yermasoyia Reservoir,Cyprus

The Yermasoyia Reservoir is located northeast of the town of Limassol, Cyprus. The storage capacity of the reservoir is 13·6 × 10⁶ m³. The basin area of the Yermasoyia River, which feeds the reservoir, totals 122·5 km². This study aims to estimate the mean annual deposition amount in the reservoir, which originates from the corresponding basin. For the estimate of the mean annual sediment inflow into the reservoir, two mathematical models are used alternatively. Each model consists of three submodels: a rainfall‐runoff submodel, a soil erosion submodel and a sediment transport submodel for streams. In the first model, the potential evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Schmidt and the sediment transport submodel of Yang are used. In the second model, the actual evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Poesen and the sediment transport submodel of Van Rijn are used. The deposition amount in the reservoir is estimated by means of the diagram of Brune, which delivers the trap efficiency of the reservoir. Daily rainfall data from three rainfall stations, and daily values of air temperature, relative air humidity and sunlight hours from a meteorological station for four years (1986–89) were available. The computed annual runoff volumes and mean annual soil erosion rate are compared with the respective measurement data. Copyright © 2006 John Wiley & Sons, Ltd.     

Characteristics of intense rainfall over Gujarat State (India) based on percentile criteria

The study focuses on the spatial and temporal variations of intense/extreme rainfall events over Gujarat State (India) during the period 1970–2014. Average monsoon rainfall for the state shows a significant increasing trend, with an increase of 48 mm/decade. Some of the stations in the Saurashtra region show a statistically significant increasing trend but none of the stations in the state show a decreasing trend. The increasing trend in monsoon rainfall is very significant for the past three decades, with an increase of 167 mm/decade. Instead of fixed absolute threshold values, relative threshold values of rainfall corresponding to the 95th, 98th, 99th and 99.5th percentiles for each station have been proposed to represent heavy, very heavy, intense and extreme rainfall, which varied between 70–120, 105–160, 130–210 and 165–280 mm, respectively. Significant increasing trends are observed for the frequency of heavy and very heavy rainfall events over the state.     

Changes in daily maximum temperature extremes across India over 1951–2014 and their relation with cereal crop productivity

This study used gridded daily maximum temperature data (1°?×?1°) for 1951–2014 period to analyze the trend in monthly extreme warm days (ExWD) and changes in its probability distribution in each grid. It also analyzed the trend in spatial spread of annual ExWD over the study period at four exceedance levels and further related the number of ExWDs with cereal crop productivity of India. Extreme warm days have increased throughout India but were statistically significant in 42% grids. The increase was consistent over all the months in north-eastern region, southern plateau and both the coastal plains. It also increased significantly over north-western and central India during April to June summer period. The probability distribution of ExWD also changed significantly in many grids, especially in southern plateau and both the coastal plains. The changes indicated increased frequency in the existing levels of extremes and new occurrences of higher frequency of extremes. The analysis of land area affected by different levels of extremes indicated significant increase, with the rate being highest for higher extremes. In terms of extreme warm day temperatures, the study identified southern plateau, east and west coast plains, and north-eastern India as highly vulnerable. Using copula probability model, study showed that increase in ExWD from 20 to 60% may increase the probability of 5% or more yield loss from 17 to 53% for Kharif cereals, 11 to 43% for Rabi cereals and 19 to 63% for wheat crop. The results may be used for devising zone specific adaptation strategies.     

Water balance of the Sudanese savannah woodland region

Abstract

The annual water balance for 39 grid cells covering the savannah woodland region of Sudan (10–16°N; 21–36°E) was determined and regional maps produced. Long-term (1961–1990) mean monthly climate data, National Forest Inventory data and Harmonized World Soil Database data for arenosols and vertisols, the two dominant soil types in the region, were used. Model validation was performed using daily data from a site in one of the grid cells and inter-annual (1961–1990) variation examined for another grid cell. Rainfall varied from 147 to 732 mm and only exceeded evapotranspiration for 18 of the grid cells, resulting in a small increase in soil moisture and runoff. Evapotranspiration accounted for, on average, 96% of rainfall and there was little difference between soil types. Drainage only occurred from AR soils and for four of the grid cells. Runoff varied from 0 to 89 mm for arenosols and from 0 to 109 mm for vertisols. The study provided useful insights into the spatial variability in water balance components across the region.

Editor D. Koutsoyiannis; Associate editor D. Gerten     

Long‐term change of daily and multi‐daily precipitation in southern Sweden

Daily rain series from southern Sweden with records dating back to the 1870s have been analysed to investigate the trends of daily and multi‐day precipitation of different return periods with emphasis on the extremes. Probabilities of extreme storms were determined as continuously changing values based on 25 years of data. An extra set of data was used to investigate changes in Skåne, the southernmost peninsula of Sweden. Another 30‐year data set of more than 200 stations of a dense gauge network in Skåne was used to investigate the relation between very large daily rainfall and annual precipitation. The annual precipitation has increased significantly all over southern Sweden due to increased winter precipitation. There is a trend of increasing maximum annual daily precipitation at only one station, where the annual maximum often occurs in winter. The number of events with a short return period is increasing, but the number of more extreme events has not increased. Daily and multi‐daily design storms of long return periods determined from extreme value analysis with updating year by year are not higher today than during the last 100 years. The largest daily storms are not related to stations with annual rainfall but seem to occur randomly. Copyright © 2013 John Wiley & Sons, Ltd.     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.     

Spatial distribution and temporal trends in daily and monthly precipitation concentration indices in the upper reaches of the Huai River, China

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.     

Assessing the relationships between elevation and extreme precipitation with various durations in southern Taiwan using spatial regression models

A spatially autocorrelated effect exists in precipitation of a mountainous basin. This study examines the relationship between maximum annual rainfall and elevation in the Kaoping River Basin of southern Taiwan using spatial regression models (i.e. geographically weighted regression (GWR), simultaneous autoregression (SAR), and conditional autoregression (CAR)). Results show that the GWR, SAR, and CAR models can improve spatial data fitting and provide an enhanced estimation for the rainfall–elevation relationship than the ordinary least squares approach. In particular, GWR achieves the most accurate estimation, and SAR and CAR achieve similar performance in terms of the Akaike information criterion. The relationship between extreme rainfall and elevation for longer duration is more concise than that for short durations. Results show that the spatial distribution of precipitation depends on elevation and that rainfall patterns in study area are heterogeneous between the southwestern plain and the eastern mountain area. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatio-temporal dynamics of sediment transport in lesser Himalayan catchments,India

Sediment transport from mountainous to lowland areas is considered one of the most important geomorphological processes. In the present study, variations in transported sediment loads and dissolved loads have been studied over 3 years (2008–2011) for two forested catchments located in the Lesser Himalayan region of India. Seasonal and annual suspended sediment flux was strongly influenced by amounts of rainfall and streamflow. On average, 93% of annual load was produced during the monsoon, of which 62–78% occurred in only five peak events. Sediment production by the degraded forest catchment (Bansigad) was 1.9-fold (suspended sediment load) to 5.9-fold (bedload) higher than the densely forested catchment (Arnigad). The dissolved organic matter potentially influences total dissolved solids in the stream. Heavy rainfall triggers both stream discharge and landslides, which lead to higher bedload transport. Total denudation rates for Arnigad and Bansigad were estimated at 0.68 and 1.02 mm?year^?1, respectively.     

On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia

Abstract

The applicability of two versions of the Bartlett Lewis rectangular pulse model, the original and the modified model, is discussed for describing the temporal and spatial variation of rainfall patterns observed at 15 raingauge stations in Peninsular Malaysia over the period 1971–2008; 17 different sets of moment combinations are fitted to these models based on the generalized method of moments approach. The common statistics included in all sets are the mean, variance, lag-1 autocorrelation and the probability of dry based on the hourly rainfall data. The analysis was carried out on hourly rainfall data from all 15 stations for all months of the year. Two stations, Petaling Jaya and Kemaman, located on the west and east coasts of the Peninsula, respectively, are considered for illustration of the results, taking the months of July and November, which correspond to the driest and wettest months, corresponding to the southwest monsoon (May–August) and northeast monsoon (November–February), respectively. The best moment combination found for the illustrative results is based on the common statistics, as well as the mean and variance based on 24-h aggregated rainfall data, the inclusion of which successfully improved the model performance; the errors were significantly reduced. It was also found that the performance of the fitted models based on the mean absolute deviate error varies according to the type of Bartlett Lewis model applied: errors are much smaller for the fitted model based on the modified model as compared to the original model. In addition, the fitted statistics: mean, lag-1 autocorrelation and probability of dry are quite well fitted for several aggregated time scales; however, the variances are underestimated in both models for all aggregated time scales, particularly in the case of the original model. The results of extreme value analysis indicate that the modified model failed to reproduce the annual hourly and daily rainfall extremes satisfactorily.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Hanaish, I.S., Ibrahim, K., and Jemain, A.A., 2013. On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia. Hydrological Sciences Journal, 58 (8), 1690–1703.     

Use of remote sensing,GIS and C++ for soil erosion assessment in the Shakkar River basin,India

Soil is an essential resource for human livelihoods. Soil erosion is now a global environmental crisis that threatens the natural environment and agriculture. This study aimed to assess the annual rate of soil erosion using distributed information for topography, land use and soil, with a remote sensing (RS) and geographical information system (GIS) approach and comparison of simulated with observed sediment loss. The Shakkar River basin, situated in the Narsinghpur and Chhindwara districts of Madhya Pradesh, India, was selected for this study. The universal soil loss equation (USLE) with RS and GIS was used to predict the spatial distribution of soil erosion occurring in the study area on a grid-cell basis. Thematic maps of rainfall erosivity factor (R), soil erodibility factor (K), topographic factor (LS), crop/cover management factor (C), and conservation/support practice factor (P) were prepared using annual rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and a satellite image of the study area in the GIS environment. The annual rate of soil erosion was estimated for a 15-year period (1992–2006) and was found to vary between 6.45 and 13.74 t ha^?1 year^?1, with an average annual rate of 9.84 t ha^?1 year^?1. The percentage deviation between simulated and observed values varies between 2.68% and 18.73%, with a coefficient of determination (R²) of 0.874.     

Long-term rainfall trends and change points in hot and cold arid regions of India

This study examined trends and change points in 100-year annual and seasonal rainfall over hot and cold arid regions of India. Using k-means clustering, 32 stations were classified into two clusters: the coefficient of variation for annual and seasonal rainfall was relatively high for Cluster-II compared to Cluster-I. Short-term and long-term persistence was more dominant in Cluster-II (entirely arid) and Cluster-I (partly arid), respectively. Trend tests revealed prominent increasing trends in annual and wet season rainfall of Cluster-II. Dry season rainfall increased by 1.09 mm year^?1 in the cold arid region. The significant change points in annual and wet season rainfall mostly occurred in the period 1941–1955 (hot and cold), and in the dry season in the period 1973–1975 (hot arid) and in 1949 (cold arid). The findings are useful for managing a surplus or deficiency of rainwater in the Indian arid region.

EDITOR A. Castellarin; ASSOCIATE EDITOR S. Kanae