Runoff Index Research Articles

Copula-based probability of concurrent hydrological drought in the Poyang lake-catchment-river system (China) from 1960 to 2013

Investigation of concurrent hydrological drought events is helpful for understanding the inherent mechanism of hydrological extremes and designing corresponding adaptation strategy. This study investigates concurrent hydrological drought in the Poyang lake-catchment-river system from 1960 to 2013 based on copula functions. The standard water level index (SWI) and the standard runoff index (SRI) are employed to identify hydrological drought in the lake-catchment-river system. The appropriate marginal distributions and copulas are selected by the corrected Akaike Information Criterion and Bayesian copulas selection method. The probability of hydrological drought in Poyang Lake in any given year is 16.6% (return period of 6years), and droughts occurred six times from 2003 to 2013. Additionally, the joint probability of concurrent drought events between the lake and catchment is 10.1% (return period of 9.9years). Since 2003, concurrent drought has intensified in spring due to frequent hydrological drought in the catchment. The joint probability of concurrent drought between the lake and the Yangtze River is 11.5% (return period of 8.7years). This simultaneous occurrence intensified in spring, summer and autumn from 2003 to 2013 due to the weakened blocking effect of the Yangtze River. Notably, although the lake drought intensified in winter during the past decade, hydrological drought in the catchment and the Yangtze River did not intensify simultaneously. Thus, this winter intensification might be caused by human activities in the lake region. The results of this study demonstrate that the Poyang lake-catchment-river system has been drying since 2003 based on a statistical approach. An adaptation strategy should be urgently established to mitigate the worsening situation in the Poyang lake-catchment-river system.

Defining Runoff Indices and Analyzing Their Relationships with Associated Precipitation and Temperature Indices for Upper River Basins in the Northwest Arid Region of China

The northwest arid region (NAR) of China, located in a cold region, has been experiencing extreme weather and runoff events for years. Summer (from June to August) is the main season for forming runoff in this region. Summer runoff is contributed by glacial runoff in addition to precipitation in glacierized basins. The upper basins of Hei River, Shule River, Kaidu River, and Manas River with different glacier coverage and available daily average discharge data were selected in this study. Two runoff indices—maximum discharge difference (MDD) and accumulated direct discharge (ADD)—were defined and calculated for each runoff event in the time series of daily average discharge during 1961–2007. To provide scientific knowledge for managing water resources and preventing disasters, the relationships between summer runoff indices and their associated precipitation and temperature variables were obtained by linear regression analysis. Results suggest that the regulation of glacier on runoff is more significant with the increase of glacier coverage.

Recent Patterns in Climate, Vegetation, and Forest Water Use in California Montane Watersheds

California has recently experienced one of the worst droughts on record, negatively impacting forest ecosystems across the state. As a major source of the region’s water supply, it is important to evaluate the vegetation and water balance response of these montane forested watersheds to climate variability across the range of rain- to snow-dominated precipitation regimes. The Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI) were used to capture the hydrologic drought signal, and MODIS vegetation indices (i.e., the normalized difference vegetation index and the enhanced vegetation index) were used to evaluate the vegetation and evapotranspiration response in three headwater catchments. The study catchments comprised a low elevation rain-dominated site (Caspar Creek) on the northern California coast, a mid-elevation site with a mix of rain and snow (Providence Creek) in the California Sierra Nevada, and a high elevation snow-dominated site (Bull Creek) in the Sierra Nevada. Lowest SPI values occurred in the third drought year of 2014 for all sites. Lowest SRI was in 2014 for Caspar, but in 2015 for Providence and Bull, reflecting differences in snowpack-delayed runoff and subsurface storage capacity between the lower and higher elevation watersheds. The most accurate water balance closure using evapotranspiration estimates from vegetation indices was within 10% of measured precipitation at snow-dominated Bull. The rain-dominated Caspar watershed had the highest vegetation index values and annual evapotranspiration, with the lowest variability over the previous 13 years (2004–2016). Vegetation index values and annual evapotranspiration decreased with increasing elevation and snow contribution to precipitation. Both snow-influenced Sierra Nevada watersheds showed elevated vegetation and evapotranspiration responses to interannual climate variability. There remains a need for institutional support to expand long-term observations in remote forested mountain watersheds to monitor and research these changing and extreme environmental conditions in source watershed regions.

Hydro-meteorological drought assessment under climate change impact over the Vu Gia–Thu Bon river basin, Vietnam

ABSTRACTHydro-meteorological drought was assessed with respect to climate change over an estuary catchment Vu Gia-Thu Bon in Central Vietnam, which economy is dependent on agriculture. The fully-distributed hydrological model MIKE SHE was used to simulate river flow over the study region for the period 1991–2010. Drought were assessed using the Standardized Precipitation Index and the Standardized Runoff Index. The future climate was studied using the regional climate model Weather Research and Forecasting by downscaling an ensemble of three global climate models – CCSM3.0, ECHAM5 and MIROC-medium resolution over current (1961–1990) and future climates (2011–2040), under the A2 emissions scenario. The results suggest that, despite hotter and wetter future climate, the area is likely to suffer more from severe and extreme droughts, increasing about 100% in the median range for drought characteristics. Thus, there is a need for proper adaptation and planning for water resources management in this region.

Impacts of climate change on hydro-meteorological drought over the Volta Basin, West Africa

This study examines the characteristics of drought in the Volta River Basin (VRB), investigates the influence of drought on the streamflow, and projects the impacts of future climate change on the drought. A combination of observation data and regional climate simulations of past and future climates (1970–2013, 2046–2065, and 2081–2100) were analyzed for the study. The Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration (SPEI) were used to characterize drought while the Standardized Runoff Index (SRI) were used to quantify runoff. Results of the study show that the historical pattern of drought is generally consistent with previous studies over the Basin and most part of West Africa. RCA ensemble medians (RMED) give realistic simulations of drought characteristics and area extent over the Basin and the sub-catchments in the past climate. Generally, an increase in drought intensity and spatial extent are projected over VRB for SPEI and SPI, but the magnitude of increase is higher with SPEI than with SPI. Drought frequency (events per decade) may be magnified by a factor of 1.2 (2046–2065) to 1.6 (2081–2100) compared to the present day episodes in the basin. The coupling between streamflow and drought episodes was very strong (P<0.05) for the 1–16-year band before the 1970 but showed strong correlation all through the time series period for the 4–8-years band. Runoff was highly sensitive to precipitation in the VRB and a 2–3month time lag was found between drought indices and streamflow in the Volta River Basin. Results of this study may guide policymakers in planning how to minimize the negative impacts of future climate change that could have consequences on agriculture, water resources and energy supply.

Analysis of meteorological and hydrological droughts in the Niger-South Basin, Nigeria

Information gained from drought analysis can serve as the basis for water resources planning and management under the prevailing climate change condition especially at the basin scale. The aim of this work is to apply two meteorological drought indices - Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and a hydrological drought index - Standardized Runoff Index (SRI) to investigate the occurrence of drought in the Niger-South Basin (NSB), a sub-catchment of the Niger River Basin in Nigeria, during the period 1970–2008. The results showed that the period between 1970 and 1981 was dominated by wet conditions; second, from 1982 to 1998, a period of droughts ranging from moderate dry to extreme dry alternated with moderate wet conditions, while the third period beginning from 1999 to 2008 displayed another round of severe droughts sparingly intercepted by occasional moderate wet conditions. High correlation values of between 0.66 (at 3-month scale) and 0.56 (at 12-month scale) show comparativeness in the performance of the two drought indices. For the hydrological drought, a severe drought was observed in 1982 and near normal and moderately wet since 1997. The higher agreement between the SRI and SPEI, suggests that hydrological droughts are more affected by temperature (warming) than precipitation (drying) in the basin. Further analysis of the frequency of the various conditions shows that it has been more of near normal conditions (>60%), while extremely dry and wet conditions (2% each) have been very rare. However, given the projected global warming conditions, a reversal of the present normal condition might be witnessed in the nearest future, hence, the results of this study can serve as a basis for effective water resources planning and management in the basin.

Utilization of the Bayesian Method to Improve Hydrological Drought Prediction Accuracy

This study established a hydrological drought forecasting system based on the Bayesian method and evaluated its utilization for South Korea. The regression result between Historical Runoff (HR) and Ensemble Streamflow Prediction Runoff (ESP_R) was used as prior information in the Bayesian method. Additionally Global seasonal forecast System 5 Runoff (GS5_R) produced using a dynamic prediction method was used in a likelihood function. Bayesian Runoff (BAY_R), as posterior information, was generated and compared with the ESP_R and GS5_R results for predictive ability evaluation. The Standardized Runoff Index (SRI) was selected for the drought prediction, and the BAY_SRI, GS5_SRI and ESP_SRI were computed using BAY_R, GS5_R and ESP_R, respectively. The Correlation Coefficient (CC), Nash-Sutcliffe Efficiency (NSE) and Receiver Operating Characteristic (ROC) score of BAY_SRI were the highest, and the Root Mean Square Error (RMSE) of BAY_SRI was the lowest among the methods. The Bayesian method improved the behavioral and quantitative error of drought prediction and the predictive ability of the occurrence of drought. In particular, the simulation accuracy was significantly improved during the flood season. Additionally, BAY_SRI represented past drought scenarios better than did the other two methods. Overall, we found that the Bayesian method could be applied for hydrological drought predictions for based on 1- and 2-month lead times.

WATER SUPPLY RESERVOIR OPERATION IN RELATION TO CLIMATE VARIABILITY: PIRAPAMA RIVER BASIN (PERNAMBUCO-BRAZIL)

The vulnearability of water resources systems is highly influenced by the climate variability of the region. The effects are amplified when the region has high population density and important economic activities such as the Recife Metropolitan Region (RMR), whose population is 3.8 million inhabitants, corresponding to 51% of the urban population in Pernambuco State. The Pirapama reservoir was designed to produce 5.6 m3/s, which corresponds to 37% of the total water demand of the RMR. The objective of the paper is to define strategies for the Pirapama reservoir operation by using guide curves and taking into account the climate variability, particularly drought events, to minimize or even avoid the conditions of rationing and collapse of its storage. The rainfall-runoff model SMAP was used to simulate input streamflow in the period 1933-2014 and the water allocation model Acquanet was used to simulate the operation rules proposed. The guide curves were defined based on the Standard Runoff Index, which classify the input inflow in drought categories. For each drought category, a response goal was defined for withdrawal reduction. This strategy may be an efficient tool to deal with the climate variability present in Northeast Brazil, which can be amplified with the effects of the climate change. In this sense, the development of sustainable operation rules can be considered an adaptation measure for reducing the impacts of possible climate changes in the future.

WATER SUPPLY RESERVOIR OPERATION IN RELATION TO CLIMATE VARIABILITY: PIRAPAMA RIVER BASIN (PERNAMBUCO-BRAZIL)

The vulnearability of water resources systems is highly influenced by the climate variability of the region. The effects are amplified when the region has high population density and important economic activities such as the Recife Metropolitan Region (RMR), whose population is 3.8 million inhabitants, corresponding to 51% of the urban population in Pernambuco State. The Pirapama reservoir was designed to produce 5.6 m3/s, which corresponds to 37% of the total water demand of the RMR. The objective of the paper is to define strategies for the Pirapama reservoir operation by using guide curves and taking into account the climate variability, particularly drought events, to minimize or even avoid the conditions of rationing and collapse of its storage. The rainfall-runoff model SMAP was used to simulate input streamflow in the period 1933-2014 and the water allocation model Acquanet was used to simulate the operation rules proposed. The guide curves were defined based on the Standard Runoff Index, which classify the input inflow in drought categories. For each drought category, a response goal was defined for withdrawal reduction. This strategy may be an efficient tool to deal with the climate variability present in Northeast Brazil, which can be amplified with the effects of the climate change. In this sense, the development of sustainable operation rules can be considered an adaptation measure for reducing the impacts of possible climate changes in the future.

Characterization of Droughts in Humid Subtropical Region, Upper Kafue River Basin (Southern Africa)

In this study, an integrated approach involving multiple standardized indicators and hydrological modeling (Soil and Water Assessment Tool, SWAT) was evaluated to reconstruct and characterize meteorological, agricultural and hydrological droughts in Upper Kafue River Basin of Zambia during 1984–2013. Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to identify meteorological droughts. Standardized Soil Moisture Index (SSI) was applied to characterize agricultural droughts and Standardized Runoff Index (SRI) was calculated to illustrate hydrological droughts. Input data for SRI and SSI computation was obtained from SWAT model which simulated daily and monthly runoff well with Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) greater than 0.65. The results showed that: (1) all indices were able to detect temporal variability of major drought events in a humid subtropical basin in Southern Africa; (2) SWAT successfully simulated runoff and soil moisture although soil moisture requires further calibration to increase accuracy; (3) the average duration and intensity for meteorological droughts at three-month time scale were lower but frequencies were higher compared to agricultural and hydrological droughts at 3- and 12-month aggregates; and (4) drought events exhibited a negative trend as evaluated by Mann–Kendall on SPEI, indicating an increase in drought severity, and correlation analysis between SPEI and SRI revealed that SPEI at 9–15 months has a strong link with hydrological conditions. This study showed that a comprehensive assessment of droughts by integrating multiple variables provided a versatile tool for drought monitoring and mitigation.

Multilevel Drought Hazard Assessment under Climate Change Scenarios in Semi-Arid Regions—A Case Study of the Karkheh River Basin in Iran

Studies using Drought Hazard Indices (DHIs) have been performed at various scales, but few studies associated DHIs of different drought types with climate change scenarios. To highlight the regional differences in droughts at meteorological, hydrological, and agricultural levels, we utilized historic and future DHIs derived from the Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Soil Water Index (SSWI), respectively. To calculate SPI, SRI, and SSWI, we used a calibrated Soil and Water Assessment Tool (SWAT) for the Karkheh River Basin (KRB) in Iran. Five bias-corrected Global Circulation Models (GCMs) under two Intergovernmental Panel on Climate Change (IPCC) scenarios projected future climate. For each drought type, we aggregated drought severity and occurrence probability rate of each index into a unique DHI. Five historic droughts were identified with different characteristics in each type. Future projections indicated a higher probability of severe and extreme drought intensities for all three types. The duration and frequency of droughts were predicted to decrease in precipitation-based SPI. However, due to the impact of rising temperature, the duration and frequency of SRI and SSWI were predicted to intensify. The DHI maps of KRB illustrated the highest agricultural drought exposures. Our analyses provide a comprehensive way to monitor multilevel droughts complementing the existing approaches.

Cartografia digital para estimativa de escoamento superficial visando ao planejamento urbano

RESUMO O trabalho foi desenvolvido na Bacia Hidrográfica do Córrego Caçula, município de Ilha Solteira (SP, Brasil), e teve como finalidade estimar o potencial de escoamento superficial com base em metodologias de cartografia apoiadas em técnicas de tratamento digital de dados objetivando baixo custo e rapidez no processo de análise com vistas a subsidiar o planejamento urbano. O método de curva número (CN), desenvolvido pelo Soil Conservation Service (SCS), foi utilizado para determinação do potencial de escoamento superficial combinando informações de uso e ocupação do solo e tipos de solo presentes na bacia. As cartas de uso e ocupação foram produzidas por meio de imagens de satélite dos anos de 2001 e 2009, possibilitando considerar cenário passado e recente para verificar a influência das mudanças de uso do solo no escoamento superficial. Foi possível averiguar que as modificações no uso e na ocupação ocorridas no período resultaram em mudanças nos índices de escoamento superficial, particularmente em função do crescimento da área urbanizada e de plantio de cana-de-açúcar em substituição a pastagens. Os resultados mostraram forte influência do uso do solo nos valores de escoamento obtidos, e as mudanças de uso, sobretudo de pastagem para cultura de cana-de-açúcar, apontaram fortes variações nos valores obtidos. Em geral, os resultados permitiram avaliar potencialidades e limitações para a expansão urbana, indicando áreas carentes de estudos mais detalhados visando à solução de problemas locais.

Development of an operational low-flow index for hydrological drought monitoring over Europe

ABSTRACTNear real-time monitoring of hydrological drought requires the implementation of an index capable of capturing the dynamic nature of the phenomenon. Starting from a dataset of modelled daily streamflow data, a low-flow index was developed based on the total water deficit of the discharge values below a certain threshold. In order to account for a range of hydrological regimes, a daily 95th percentile threshold was adopted, which was computed by means of a 31-day moving window. The observed historical total water deficits were statistically fitted by means of the exponential distribution and the corresponding probability values were used as a measure of hydrological drought severity. This approach has the advantage that it directly exploits daily streamflow values, as well as allowing a near real-time update of the index at regular time steps (i.e. 10 days, or dekad). The proposed approach was implemented on discharge data simulated by the LISFLOOD model over Europe during the period 1995–2015; its reliability was tested on four case studies found within the European drought reference database, as well as against the most recent summer drought observed in Central Europe in 2015. These validations, even if only qualitative, highlighted the ability of the index to capture the timing (starting date and duration) of the main historical hydrological drought events, and its good performance in comparison with the commonly used standardized runoff index (SRI). Additionally, the spatial evolution of the most recent event was captured well in a simulated near real-time test case, suggesting the suitability of the index for operational implementation within the European Drought Observatory.

Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model

Prediction of drought plays an important role in drought preparedness and mitigation, especially because of large impacts of drought and increasing demand for water resources. An important aspect for improving drought prediction skills is the identification of drought predictability sources. In general, a drought originates from precipitation deficit and thus the antecedent meteorological drought may provide predictive information for other types of drought. In this study, a hydrological drought (represented by Standardized Runoff Index (SRI)) prediction method is proposed based on the meta-Gaussian model taking into account the persistence and its prior meteorological drought condition (represented by Standardized Precipitation Index (SPI)). Considering the inherent nature of standardized drought indices, the meta-Gaussian model arises as a suitable model for constructing the joint distribution of multiple drought indices. Accordingly, the conditional distribution of hydrological drought can be derived analytically, which enables the probabilistic prediction of hydrological drought in the target period and uncertainty quantifications. Based on monthly precipitation and surface runoff of climate divisions of Texas, U.S., 1-month and 2-month lead predictions of hydrological drought are illustrated and compared to the prediction from Ensemble Streamflow Prediction (ESP). Results, based on 10 climate divisions in Texas, show that the proposed meta-Gaussian model provides useful drought prediction information with performance depending on regions and seasons.

Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins

Recent climate change impact studies studies have presented conflicting results regarding the largest source of uncertainty in essential hydrological variables, especially streamflow and derived characteristics that describe the evolution of drought events. Part of the problem arises from the lack of a consistent framework to address compatible initial conditions for the impact models and a set of standardized historical and future forcings. The ISI-MIP2 project provides a good opportunity to advance our understanding of the propagation of forcing and model uncertainties on to century-long time series of drought characteristics using an ensemble of hydrological model (HM) projections across a broad range of climate scenarios and regions. To achieve this goal, we used six regional preconditioned hydrological models set up in seven large river basins: Upper-Amazon, Blue-Nile, Ganges, Upper-Niger, Upper-Mississippi, Rhine, and Upper-Yellow. These models were forced with bias-corrected outputs from five CMIP5 general circulation models (GCMs) under two extreme representative concentration pathway scenarios (i.e., RCP2.6 and RCP8.5) for the period 1971-2099. The simulated streamflow was transformed into a monthly runoff index (RI) to analyze the attributions of the GCM and HM uncertainties on to drought magnitudes and durations over time. The results indicated that GCM uncertainty mostly dominated over HM uncertainty for the projections of runoff drought characteristics, irrespective of the selected RCP and region. In general, the overall uncertainty increased with time. The uncertainty in the drought characteristics increased as the radiative forcing of the RCP increased, but the propagation of the GCM uncertainty on to a drought characteristic depended largely upon the hydro-climatic regime. Although our study emphasizes the need for multi-model ensembles for the assessment of future drought projections, the agreement between the GCM forcings was still too weak to draw conclusive recommendations.

Drought class transition analysis through different models: a case study in North China

The standardized precipitation index (SPI) and standardized runoff index (SRI) are computed for several gauge stations in Panjiakou Reservoir catchment of Luanhe Basin, a drought prone region of North China. Based on the SPI and SRI time series, two different models, a weighted Markov chain model and a Volterra adaptive filter model for chaotic time series, were established to predict drought classes and achieve both short- and long-term drought forecasting. These approaches were compared with a three-dimensional (3D) loglinear model, reported in our previous work. It was observed that all the three models have pros and cons when applied to drought prediction in Panjiakou Reservoir catchment. The 3D loglinear model is able to forecast drought class within 1 month. However, its predicting accuracy declines with the increase of prediction time scale, and this confines its application. The weighted Markov chain model is a useful tool for drought early warning. Its precision, which is significantly related to the stable condition of drought classes, is highest for Non-drought, followed by Moderate and Severe/Extreme drought, and lowest for Near-normal. The Volterra adaptive filter model for chaotic time series combined the phase space reconstruction technique, Volterra series expansion technique and adaptive filter optimization technique, and was for the first time used in a drought class transition study. This model is effective and highly precise in long-term drought prediction (for example, 12 months). It is able to provide reliable information for the medium- and long-term decisions and plans for water resources systems.

Comparison of two hydrological drought indices

Summary Drought is a naturally occurring periodical event associated with significant decrease of water availability over a region. Drought, being a complex in nature it is difficult to define, quantify and monitor. Drought is mainly classified into meteorological drought, hydrological drought and agricultural drought. Among these classifications, assessment of hydrological drought has more importance in the water resources management perspective. Objective of this study is to analyse multi-time step hydrological drought by Stream flow Drought Index (SDI) and Standardized Runoff Index (SRI). To obtain these indices, 36 years (1972–2007) of daily discharge data, measured in Ghataprabha river basin (a sub basin of Krishna river) is considered. Results of both indices indicate moderate drought between 1986–1988 and 2001–2005 continuously. While comparing both indices, there is a good correlation between 9-month SRI and SDI is observed and it increases for 12-month SRI and SDI. This study may help to choose the appropriate drought indices among SRI and SDI for different lengths of drought studies.

Evidence and Causes of Spatiotemporal Changes in Runoff and Sediment Yield on the Chinese Loess Plateau

AbstractClimate change and human activities are strongly influencing the eco‐hydrological processes of the Chinese Loess Plateau. It is challenging to investigate the spatiotemporal changes of water and sediment yields and identify their potential causes. In this study, we used the annual runoff index (WI) and specific sediment yield (SSY) derived from 58 hydrological stations to quantify the changes and attempted to explain their potential causes. The WI exhibited significant (P &lt; 0.05) decrease ranging from −0.1 to −2.6 mm yr−1 during 1957–2012 in 44 sub‐catchments. Similarly, the SSY in 52 sub‐catchments reduced in a range between −2.86 and −636 Mg km−2 yr−1. The region of Toudaoguai–Longmen has extremely high SSY ranging from 8000 to 41 000 Mg km−2 yr−1 during 1957–1969. Budget analysis suggested that the area of Lanzhou–Toudaoguai contributed limited sediment but extracted large amount of water. The areas with negative SSY were increasing and mainly distributed along the mainstream of the Yellow River. The Loess plateau was becoming drier and warmer since the 1950s, whereas the intensive human activities including water withdrawal, soil and water conservation projects and the operation of dams and reservoirs are the dominant factors for the decline in WI and SSY on the Loess Plateau. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

The nature of drought conditions is estimated using a range of indices describing different aspects of drought events. Three drought indices are evaluated, namely the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Runoff Index (SRI), using observed hydroclimatic data and applying them to hydro-meteorological projections into the 21st century. The first two indices are evaluated using only meteorological variables and from this point of view, are better suited to meteorological drought projections than the third index, SRI, which is based on catchment discharge and represents hydrological drought. We assess information contained in those indices and their suitability to catchment scale climate projection drought assessment in ten selected Polish catchments, representing different hydro-climatic conditions, which are used as a case study. Projections of climatic variables (precipitation and temperature) are obtained from the EURO-CORDEX initiative derived from seven climate models at a grid resolution of 12.5 km for the time period 1971–2100. Future runoff projections for the catchments are obtained using a conceptual rainfall-runoff model (HBV). The results of analyses of indices based on observations in the reference period show consistent estimates for most of the catchments. Hydro-meteorological climate model projections for three periods, including the reference period 1971–2000, and two 30-year periods, near-future 2021–2050 and far-future 2071–2100, are used to estimate changes of future drought conditions in the catchments studied. The results show a substantial variation of temporal drought patterns over the catchments and their dependence on projected precipitation and temperature variables and the type of indices applied. Of the three indices studied, only SPEI projections indicate drier conditions in the catchments in the far-future period. The other two indices, SPI and SRI, indicate wetter climates in the future.

Transitional variations and risk of hydro-meteorological droughts in the Tarim River basin, China

The Tarim River basin, China, is a typical arid inland river basin in China. Management of water resources and agricultural development rely heavily on the understanding of droughts. In this study, an integrated drought index is proposed, based on the Standardized Precipitation Evapotranspiration Index and the Standardized Runoff Index, and then the changing properties of drought regimes have been analyzed using a Markov Chain model. Results indicate that: (1) the Kaidu and Aksu Rivers are dominated by prompt transition between hydrological and meteorological droughts. Long-lasting droughts heavily impact agricultural development in the Kaidu and Yarkand River basins; (2) the Kaidu and Aksu River basins are influenced mainly by hydro-meteorological droughts and hydrological drought is dominant in the Yarkand River basin; (3) different drought conditions are the results of different sources of river runoff. Increasing precipitation alleviate droughts in the Tarim River basin. However, a drying tendency can still be found in the Kaidu River basin; (4) higher probability is detected for the transition from both meteorological and hydrological wet to both meteorological and hydrological dry, implying that the Tarim River basin is sensitive to both meteorological and hydrological droughts. Results of this study are of practical value for the regional management of water resources, planning of agricultural irrigation, and measures for mitigation of hydrological and meteorological droughts.