Trend and persistence of precipitation under climate change scenarios for Kansabati basin,India

With increasing uncertainties associated with climate change, precipitation characteristics pattern are receiving much attention these days. This paper investigated the impact of climate change on precipitation in the Kansabati basin, India. Trend and persistence of projected precipitation based on annual, wet and dry periods were studied using global climate model (GCM) and scenario uncertainty. A downscaling method based on Bayesian neural network was applied to project precipitation generated from six GCMs using two scenarios (A2 and B2). The precipitation values for any of three time periods (dry, wet and annual) do not show significant increasing or decreasing trends during 2001–2050 time period. There is likely an increasing trend in precipitation for annual and wet periods during 2051–2100 based on A2 scenario and a decreasing trend in dry period precipitation based on B2 scenario. Persistence during dry period precipitation among stations varies drastically based on historical data with the highest persistence towards north‐west part of the basin. Copyright © 2009 John Wiley & Sons, Ltd.     

Downscaling of precipitation for climate change scenarios: A support vector machine approach

The Climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, general circulation models (GCMs), which are among the most advanced tools for estimating future climate change scenarios, operate on a coarse scale. Therefore the output from a GCM has to be downscaled to obtain the information relevant to hydrologic studies. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling of precipitation at monthly time scale. The effectiveness of this approach is illustrated through its application to meteorological sub-divisions (MSDs) in India. First, climate variables affecting spatio-temporal variation of precipitation at each MSD in India are identified. Following this, the data pertaining to the identified climate variables (predictors) at each MSD are classified using cluster analysis to form two groups, representing wet and dry seasons. For each MSD, SVM- based downscaling model (DM) is developed for season(s) with significant rainfall using principal components extracted from the predictors as input and the contemporaneous precipitation observed at the MSD as an output. The proposed DM is shown to be superior to conventional downscaling using multi-layer back-propagation artificial neural networks. Subsequently, the SVM-based DM is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to obtain future projections of precipitation for the MSDs. The results are then analyzed to assess the impact of climate change on precipitation over India. It is shown that SVMs provide a promising alternative to conventional artificial neural networks for statistical downscaling, and are suitable for conducting climate impact studies.     

Impact of climate change on water resources in southern Taiwan

This study investigates the impact of climate change on water resources in southern Taiwan. The upstream catchment of Shin-Fa Bridge station in the Kao-Pen Creek basin was the study area chosen herein. The historical trends of meteorological variables, such as mean daily temperature, mean daily precipitation on wet days, monthly wet days, and the transition probabilities of daily precipitation occurrence in each month, at the Kao-Hsiung meteorological station, near the catchments were detected using a non-parametric statistical test. The trends of these meteorological variables were then employed to generate runoff in future climatic conditions using a continuous rainfall–runoff model. The analytical results indicate that the transition probabilities of daily precipitation occurrence significantly influence precipitation generation, and generated runoff for future climatic conditions in southern Taiwan was found to rise during the wet season and decline during the dry season.     

Simulated runoff responses to land use in the middle and upstream reaches of Taoerhe River basin,Northeast China,in wet,average and dry years

Study on runoff variations and responses can lay a foundation for flood control, water allocation and integrated river basin management. This study applied the Soil and Water Assessment Tool model to simulate the effects of land use on annual and monthly runoff in the Middle and Upstream Reaches of Taoerhe River basin, Northeast China, under the wet, average and dry climate conditions through scenario analysis. The results showed that from the early 1970s to 2000, land use change with an increase in farmland (17.0%) and decreases in forest (10.6%), grassland (4.6%) and water body (3.1%) caused increases in annual and monthly runoff. This effect was more distinct in the wet season or in the wet year, suggesting that land use change from the early 1970s to 2000 may increase the flood potential in the wet season. Increases in precipitation and air temperature from the average to wet year led to annual and monthly (March and from June to December) runoff increases, while a decrease in precipitation and an increase in air temperature from the average to dry year induced decreases in annual and monthly (all months except March) runoff, and moreover, these effects were more remarkable in the wet season than those in the dry season. Due to the integrated effects of changing land use and climate conditions, the annual runoff increased (decreased) by 70.1 mm (25.2 mm) or 197.4% (71.0%) from the average to wet (dry) year. In conclusion, climate conditions, especially precipitation, played an important role in runoff variations while land use change was secondary over the study area, and furthermore, the effects of changes in land use and/or climate conditions on monthly runoff were larger in the wet season. Copyright © 2012 John Wiley & Sons, Ltd.     

Relationship and its instability of ENSO — Chinese variations in droughts and wet spells

Monthly data of Self-Calibrated Palmer Drought Severity Index (PDSI) from 1951 to 2000 are calculated using historical precipitation and temperature data for Chinese 160 stations. Temporal and spatial patterns of the first empirical orthogonal function (EOF) of the PDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature, which is similar to the linear PDSI trend during 1951–2000 calculated using all monthly data. The EOF analysis also reveals that the leading mode correlates significantly with ENSO events in time and space. The ENSO EOF shows that during the typical warm phase of ENSO, surface conditions are drier in most regions of China, especially North China, but wetter than normal in the southern regions of Changjiang River, and Northwest China. During the typical cold phase of ENSO, these anomalies reverse sign. From 1951 to 2000, there are large multi-year to decadal variations in droughts and wet spells over China, which are all closely related to strong El Niño events. In other words, when one strong El Niño event happens, there is a possible big variability in droughts and wet spells over China on the multi-year or decadal scale. Studies also suggest that during the last 2–3 decades climate changes over China, especially North China’s drying and northwest China’s wetting, are closely related to the shift in ENSO towards warmer events and global warming since the late 1970s. The instability of the relationship is also studied. It is revealed that there is a good correlation between ENSO and Chinese variations in droughts and wet spells in the 3–8-year band, but the correlation between ENSO and Chinese variations in droughts and wet spells is instable. Studies suggest that there are decadal changes in the correlation: the wavelet coherency between ENSO and Chinese variations in droughts and wet spells is high during 1951–1962 and 1976–1991, but low during 1963–1975 and 1992–2000.     

Trends of precipitation in Beijiang River Basin,Guangdong Province,China

An analysis of spatial and temporal trends of precipitation in Beijiang River basin, Guangdong Province, China during 1959–2003 was performed using 17 time series (including monthly, annual, wet season, dry season, early flood period and late flood period totals) both on station based and sub‐basin based data sets. Two nonparametric methods (Mann–Kendall and Sen's T) were used for data analysis. The results showed that (1) downward trends of temporal distribution were mostly detected during the early flood period, especially in May, while upward trends were observed in July and the dry season; (2) downward trends of spatial distribution were mostly detected in the southern Beijiang River basin, while upward trends were observed north of this area. Our results indicated a delayed rainy season and a northward trend of the precipitation belt compared to recent years. Copyright © 2007 John Wiley & Sons, Ltd.     

Combined analysis of precipitation and water deficit for drought hazard assessment

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.     

The spatial and temporal analysis of precipitation concentration and dry spell in Qinghai,northwest China

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.     

Analysis of agricultural drought in Iiuni,Eastern Kenya: application of a Markov model

In semi‐arid Kenya, episodes of agricultural droughts of varying severity and duration occur. The occurrence of these agricultural droughts is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop performance and yield. The objective of this study was to stochastically simulate the behaviour of dry and wet spells and rainfall amounts in Iiuni watershed, Kenya. The stochastic behaviour of the longest dry and wet spells (runs) and largest rainfall amounts were simulated using a Markov (order 1) model. There were eight raingauge stations within the watershed. The entire analysis was carried out using probability parameters, i.e. mean, variance, simple and conditional probabilities of dry and rain days. An analysis of variance test (ANOVA ) was used to establish significant differences in rainfall characteristics between the eight stations. An analysis of the number of rain days and rainfall amount per rain day was done on a monthly basis to establish the distribution and reliability of seasonal rainfall. The graphic comparison of simulated cumulative distribution functions (Cdfs) of the longest spells and largest rainfall amounts showed Markovian dependence or persistence. The longest dry spells could extend to 24 days in the long rainy season and 12 in the short rainy season. At 50% (median) probability level, the largest rainfall amounts were 91 mm for the long rainy season and 136 mm for the short rainy season. The short rains were more reliable for crop production than the long rains. The Markov model performed well and gave adequate simulations of the spells and rainfall amounts under semi‐arid conditions. Copyright © 2004 John Wiley & Sons, Ltd.     

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.     

VHF radar observed characteristics of convectively generated gravity waves during wet and dry spells of Indian summer monsoon

A powerful VHF radar observed characteristics of Convectively generated Gravity Waves (CGW) excited during the wet and dry spells of Indian summer monsoon over a tropical station Gadanki (13.5°N, 79.2°E) are discussed. The characteristics of gravity waves in the lower stratosphere during these two spells are discussed in terms of their wavelet spectra along with height–time sections of vertical velocity. A total of 31 events are analyzed and in more than 50% of the events, the lower stratospheric gravity wave amplitudes were found to be relatively large in dry spell compared to that in the wet spell. The wavelet analysis of lower stratospheric vertical velocities showed a dominant periodicity of about ～20–40 min in wet spell and ～10–20 min in dry spell. The analysis also indicates that wet spell is found to be more conducive for the generation of gravity waves. However, the propagation of these waves into the stratosphere is found to be more efficient in dry spell of monsoon. The strengthening/weakening of the tropical easterly jet during wet/dry spell of monsoon is found to be the main reason for the inhibited/enhanced wave activity in the lower stratosphere during wet/dry spell. The present analysis also suggests that the static stability of the mid- and upper-troposphere during these two spells have implications in the observed frequency of the CGW. Thus, the present analyses brought out for the first time the features of CGW during two distinctive regimes of convective systems and emphasized the importance of prevailing background conditions in exciting/filtering them.     

A drought climatology for Mauritius using the standardized precipitation index

This study presents a high-resolution and multi-temporal drought climatology for Mauritius based on calculated standardized precipitation index (SPI) using mean monthly rainfall for the period 1953–2007. A monthly mean SPI varying from +3.4 to ?2.7 indicates the occurrence of extremely wet and dry conditions, and collocated SPI indicates more frequent mild drought conditions. Spatial maps of rainfall trends and SPI show mostly neutral to severely dry conditions, but sparse regions of extremely wet and dry conditions are also observed. An increase in the frequency of dry years after the 1990s is noted, while most of the extreme wet conditions are found to have occurred between 1972 and 1988. More frequent short-duration wet events are observed on the 3- and 6-month time scales compared to dry events. On the 12- and 24-month time scales the frequency of both dry and wet periods is almost the same, with the dry events lasting longer.     

Evaluating the impacts of climate change and switchgrass production on a semiarid basin

Climate and land use changes greatly modify hydrologic regimes. In this paper, we modelled the impacts of biofuel cultivation in the US Great Plains on a 1061‐km² watershed using the Soil and Water Assessment Tool (SWAT) hydrologic model. The model was calibrated to monthly discharges spanning 2002–2010 and for the winter, spring, and summer seasons. SWAT was then run for a climate‐change‐only scenario using downscaled precipitation and a projected temperature for 16 general circulation model (GCM) runs associated with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 scenario spanning 2040–2050. SWAT was also run on a climate change plus land use change scenario in which Alamo switchgrass (Panicum virgatum L.) replaced native range grasses, winter wheat, and rye (89% of the basin). For the climate‐change‐only scenario, the GCMs agreed on a monthly temperature increase of 1–2 °C by the 2042–2050 period, but they disagreed on the direction of change in precipitation. For this scenario, decreases in surface runoff during all three seasons and increases in spring and summer evapotranspiration (eT) were driven predominantly by precipitation. Increased summer temperatures also significantly contributed to changes in eT. With the addition of switchgrass, changes in surface runoff are amplified during the winter and summer, and changes in eT are amplified during all three seasons. Depending on the GCM utilized, either climate change or land use change (switchgrass cultivation) was the dominant driver of change in surface runoff while switchgrass cultivation was the major driver of changes in eT. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of human activities on stream flow in the Biliu River basin,China

The obvious decline in stream flow to the Biliu River reservoir over the period 1990–2005 has raised increasing concerns. Climate change and human activities, which mainly include land use changes, hydraulic constructions and artificial water consumption, are considered to be the most likely reasons for the decline in stream flow. This study centres on a detailed analysis of the runoff response to changes in human activities. Using a distributed hydrological model, (Soil and Water Assessment Tool), we simulated runoffs under different human activity and climate scenarios to understand how each scenario impacts stream flow. The results show that artificial water consumption correlates with the precipitation (wet, normal and dry) of the year in question and is responsible for most of the decrease in runoff during each period and for each different wetness year. A Fuzzy Inference Model is also used to find the relationship between the precipitation and artificial water consumption for different years, as well as to make inferences regarding the future average impact on runoff. Land use changes in the past have increased the runoff by only a small amount, while another middle reservoir (Yunshi) has been responsible for a decrease in runoff since operation began in 2001. We generalized the characteristics of the human activities to predict future runoff using climate change scenarios. The future annual flow will increase by approximately 10% from 2011 to 2030 under normal human activities and future climate change scenarios, as indicated by climate scenarios with a particularly wet year in the next 20 years. This study could serve as a framework to analyse and predict the potential impacts of changes both in the climate and human activities on runoff, which can be used to inform the decision making on the river basin planning and management. Copyright © 2012 John Wiley & Sons, Ltd.     

Drought characterization: a probabilistic approach

Using the alternative renewable process and run theory, this study investigates the distribution of drought interval time, mean drought interarrival time, joint probability density function and transition probabilities of drought events in the Kansabati River basin in India. The standardized precipitation index series is employed in the investigation. The time interval of SPI is found to have a significant effect of the probabilistic characteristics of drought.     

The spatial and temporal analysis of dry spells in the Yellow River basin, China

In this research, drought in Yellow River basin has been studied by using dry spells. Three indices, including the maximum length (MxDS), mean length (MDS) and number of dry spells (NDS), and five periods (annual, winter, spring, summer and autumn) are considered. The results show that a south to north gradient for mean MxDS and MDS has been dominantly found in all periods except summer, in which a southwest and southeast to north gradient exists. Mean NDS shows an opposite distribution to that of mean MxDS and MDS. It is surely that the northern part of Yellow River basin, with a higher MxDS and MDS and lower NDS, is much drier than southern part in a regional scale. According to temporal analysis by using the Mann–Kendall trend method, MxDS of most stations show negative but insignificant trends during annual and winter, while the majority of stations show positive trends during spring, summer and autumn. Trends of MDS and NDS dominantly depict positive and negative for most periods, respectively. By comparing the frequency of dry spells during the ENSO events, it can be found that the frequency of intermediate and long dry spells is almost tantamount during the occurrence periods of El Niño and La Niña.     

Changes of flow regimes and precipitation in Huai River Basin in the last half century

Huai River Basin, as the sixth largest river basin in China, has a high‐regulated river system and has been facing severe water problems. In this article, the changing patterns of runoff and precipitation at 10 hydrological stations from 1956 to 2000 on the highly regulated river (Shaying River) and less‐regulated river (Huai River) in the basin are evaluated at the monthly, seasonal and annual scales using the Mann–Kendall test and simple linear regression model. The results showed that: (1) No statistically significant trends of precipitation in the upper and middle Huai River Basins were detected at the annual scale, but the trend of annual runoff at Baiguishan, Zhoukou and Fuyang stations in Shaying River decreased significantly, whereas the others were not. Moreover, the decreasing trends of runoff for most months were significant in Shaying River, although the trend of monthly precipitation decreased significantly only in April in the whole research area and the number of months in the dry season having significantly decreasing trends in runoff was more than that in the wet season. (2) The rainfall–runoff relationship was significant in both highly regulated river and less‐regulated river. In regulated river, the reservoirs have larger regulation capacity than the floodgates and thus have the smaller correlation coefficient and t‐value. In Huai River, the correlation coefficients decreased from upper stream to downstream. (3) The regulation of dams and floodgates for flood control and water supply was the principal reason for the decreasing runoff in Huai River Basin, although the decreasing precipitation in April in this basin was statistically significant. The findings are useful for recognizing hydrology variation and will provide scientific foundation to integrated water resources management in Huai River Basin. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulating precipitation in the Northeast United States using a climate-informed K-nearest neighbour algorithm

Decadal prediction using climate models faces long-standing challenges. While global climate models may reproduce long-term shifts in climate due to external forcing, in the near term, they often fail to accurately simulate interannual climate variability, as well as seasonal variability, wet and dry spells, and persistence, which are essential for water resources management. We developed a new climate-informed K-nearest neighbour (K-NN)-based stochastic modelling approach to capture the long-term trend and variability while replicating intra-annual statistics. The climate-informed K-NN stochastic model utilizes historical data along with climate state information to provide improved simulations of weather for near-term regional projections. Daily precipitation and temperature simulations are based on analogue weather days that belong to years similar to the current year's climate state. The climate-informed K-NN stochastic model is tested using 53 weather stations in the Northeast United States with an evident monotonic trend in annual precipitation. The model is also compared to the original K-NN weather generator and ISIMIP-2b GFDL general circulation model bias-corrected output in a cross-validation mode. Results indicate that the climate-informed K-NN model provides improved simulations for dry and wet regimes, and better uncertainty bounds for annual average precipitation. The model also replicates the within-year rainfall statistics. For the 1961–1970 dry regime, the model captures annual average precipitation and the intra-annual coefficient of variation. For the 2005–2014 wet regime, the model replicates the monotonic trend and daily persistence in precipitation. These improved modelled precipitation time series can be used for accurately simulating near-term streamflow, which in turn can be used for short-term water resources planning and management.     

Impact of road‐generated storm runoff on a small catchment response

The impact of road‐generated runoff on the hydrological response of a zero‐order basin was monitored for a sequence of 24 storm events. The study was conducted in a zero‐order basin (C1; 0·5ha) with an unpaved mountain road; an adjacent unroaded zero‐order basin (C2; 0·2 ha) with similar topography and lithology was used to evaluate the hydrological behaviour of the affected zero‐order basin prior to construction of the road. The impact of the road at the zero‐order basin scale was highly dependent on the antecedent soil‐moisture conditions, total storm precipitation, and to some extent rainfall intensity. At the beginning of the monitoring period, during dry antecedent conditions, road runoff contributed 50% of the total runoff and 70% of the peak flow from the affected catchment (C1). The response from the unroaded catchment was almost insignificant during dry antecedent conditions. As soil moisture increased, the road exerted less influence on the total runoff from the roaded catchment. For very wet conditions, the influence of road‐generated runoff on total outflow from the roaded catchment diminished to only 5·4%. Both catchments, roaded and unroaded, produced equivalent amount of outflow during very wet antecedent conditions on a unit area basis. The lag time between the rainfall and runoff peaks observed in the unroaded catchment during the monitoring period ranged from 0 to 4 h depending on the amount of precipitation and antecedent conditions, owing mainly to much slower subsurface flow pathways in the unroaded zero‐order basin. In contrast, the lag time in the roaded zero‐order basin was virtually nil during all storms. Copyright © 2009 John Wiley & Sons, Ltd.     

Climate change analysis on historical watershed‐scale precipitation by means of long‐term dynamical downscaling

A methodology based on long‐term dynamical downscaling to analyse climate change effects on watershed‐scale precipitation during a historical period is proposed in this study. The reliability and applicability of the methodology were investigated based on the long‐term dynamical downscaling results. For an application of the proposed methodology, two study watersheds in Northern California were selected: the Upper Feather River watershed and the Yuba River watershed. Then, precipitation was reconstructed at 3‐km spatial resolution and hourly intervals over the study watersheds for 141 water years from 1 October 1871 to 30 September 2012 by dynamically downscaling a long‐term atmospheric reanalysis dataset, 20th century global reanalysis version 2 by means of a regional climate model. The reconstructed precipitation was compared against observed precipitation, in order to assess the applicability of the proposed methodology for the reconstruction of watershed‐scale precipitation and to validate this methodology. The validation shows that the reconstructed precipitation is in good agreement with observation data. Moreover, the differences between the reconstructed precipitation and the corresponding observations do not significantly change through the historical period. After the validation, climate change analysis was conducted based on the reconstructed precipitation. Through this analysis, it was found that basin‐average precipitation has increased significantly over both of the study watersheds during the historical period. An upward trend in monthly basin‐average precipitation is not significant in wet months except February while it is significant in dry months of the year. Furthermore, peak values of basin‐average precipitation are also on an upward trend over the study watersheds. The upward trend in peak basin‐average precipitation is more significant during a shorter duration. Copyright © 2016 John Wiley & Sons, Ltd.