scholarly journals Meteorological Drought, Hydrological Drought, and NDVI in the Heihe River Basin, Northwest China: Evolution and Propagation

2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Fanglei Zhong ◽  
Qingping Cheng ◽  
Ping Wang
Keyword(s):  
River Basin ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Condition Index ◽  
Hydrological Drought ◽  
Heihe River Basin ◽  
Heihe River ◽  
Propagation Time ◽  
Peak Intensity ◽  
Positive Effect

Understanding the evolution and propagation of different drought types is crucial to reduce drought hazards in arid and semiarid regions. Here, Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Vegetation Condition Index (VCI) were used to investigate the spatiotemporal variation of different drought types and correlations between Pre (Pre-R)/post (Pos-R)-reservoir. Results showed that the average peak/intensity/duration/severity of meteorological droughts (MD) were greater in the Pre-R than in the Pos-R period in the upstream Heihe River Basin (UHRB), while there was little change between the Pre-R and Pos-R periods in the midstream Heihe River Basin (MHRB). The average peak/intensity/duration/severity of hydrological drought (HD) decreased in the mainstream for Yingluoxia (Ylx) but increased for Zhengyixia (Zyx) station in the Pos-R period. Propagation time decreased by 3 months (negative effect) in Ylx and increased by 8 months (positive effect) in Zyx compared with the Pre-R period. In the Pos-R period, propagation time increased (1–3 months) for tributaries (positive effect). Propagation times for the mainstream and tributaries varied for different seasons and time periods. Pearson’s correlation coefficient values were lower at short timescales (1–3 months) but higher at long timescales for the Pos-R period in Ylx and Zyx for SDI-1 with different timescales of SPI. The SDI and SPI had no lag in the UHRB and MHRB. However, VCI with SPI had a significant lag correlation at short timescales in the UHRB (lag 6 months) and MHRB (lag 4 months), and the VCI with SDI had a significant lag correlation for 1 month in the MHRB. The propagation time from MD to HD has been reduced for Pos-R in the UHRB. There was a positive effect (prolonged MD propagation HD time) in Pos-R but still faces serious drought stress in the MHRB.

scholarly journals Drought Characteristics and Propagation in the Semiarid Heihe River Basin in Northwestern China

2019 ◽  
Vol 20 (1) ◽  
pp. 59-77 ◽  
Author(s):  
Feng Ma ◽  
Lifeng Luo ◽  
Aizhong Ye ◽  
Qingyun Duan
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Human Activities ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Heihe River Basin ◽  
Heihe River ◽  
Propagation Time ◽  
Drought Characteristics ◽  
Hydrological Droughts

Abstract Meteorological and hydrological droughts can bring different socioeconomic impacts. In this study, we investigated meteorological and hydrological drought characteristics and propagation using the standardized precipitation index (SPI) and standardized streamflow index (SSI), over the upstream and midstream of the Heihe River basin (UHRB and MHRB, respectively). The correlation analysis and cross-wavelet transform were adopted to explore the relationship between meteorological and hydrological droughts in the basin. Three modeling experiments were performed to quantitatively understand how climate change and human activities influence hydrological drought and propagation. Results showed that meteorological drought characteristics presented little difference between UHRB and MHRB, while hydrological drought events are more frequent in the MHRB. In the UHRB, there were positive relationships between meteorological and hydrological droughts, whereas drought events became less frequent but longer when meteorological drought propagated into hydrological drought. Human activities have obviously changed the positive correlation to negative in the MHRB, especially during warm and irrigation seasons. The propagation time varied with seasonal climate characteristics and human activities, showing shorter values due to higher evapotranspiration, reservoir filling, and irrigation. Quantitative evaluation showed that climate change was inclined to increase streamflow and propagation time, contributing from −57% to 63%. However, more hydrological droughts and shorter propagation time were detected in the MHRB because human activities play a dominant role in water consumption with contribution rate greater than (−)89%. This study provides a basis for understanding the mechanism of hydrological drought and for the development of improved hydrological drought warning and forecasting system in the HRB.

scholarly journals Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in Northwestern China

2018 ◽  
Author(s):  
Feng Ma ◽  
Lifeng Luo ◽  
Aizhong Ye ◽  
Qingyun Duan
Keyword(s):  
River Basin ◽  
Climate Models ◽  
Dominant Role ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Forecast Skill ◽  
Heihe River Basin ◽  
Heihe River ◽  
Drought Forecasting

Abstract. Endorheic and arid regions around the world are suffering from serious drought problems. In this study, a drought forecasting system based on eight state-of-the-art climate models from North American Multi-Model Ensemble (NMME) and a Distributed Time-Variant Gain Hydrological Model (DTVGM) was established and assessed over the upstream and midstream of Heihe River basin (UHRB and MHRB), a typical arid endorheic basin. The 3-month Standardized Precipitation Index (SPI3) and 1-month Standardized Streamflow Index (SSI1) were used to capture meteorological and hydrological drought, and values below -1 indicate drought events. The skill of the forecasting systems was evaluated in terms of Anomaly Correlation (AC) and Brier skill score (BSS). The UHRB and MHRB showed season-dependent meteorological drought predictability and forecast skill, with higher values during winter and autumn than that during spring. For hydrological forecasts, the forecast skill in the UHRB was higher than that in MHRB. Predicting meteorological droughts more than 2 months in advance became difficult because of complex climate mechanism. However, the hydrological drought forecasts could show some skills up to 3–6 lead months due to memory of initial hydrologic conditions (ICs) during cold and dry seasons. During wet seasons, there's no skillful hydrological predictions since lead-2 month because the dominant role of meteorological forcings. During spring, the improvement of hydrological drought predictions is the most significant as more streamflow was generated by seasonal snowmelt. Besides meteorological forcings and ICs, human activities have reduced the hydrological variability and increased hydrological predictability during the wet seasons in the MHRB.

scholarly journals Seasonal drought predictability and forecast skill in the semi-arid endorheic Heihe River basin in northwestern China

2018 ◽  
Vol 22 (11) ◽  
pp. 5697-5709 ◽  
Author(s):  
Feng Ma ◽  
Lifeng Luo ◽  
Aizhong Ye ◽  
Qingyun Duan
Keyword(s):  
River Basin ◽  
Dominant Role ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Forecast Skill ◽  
Heihe River Basin ◽  
Brier Score ◽  
Heihe River

Abstract. Endorheic and arid regions around the world are suffering from serious drought problems. In this study, a drought forecasting system based on eight state-of-the-art climate models from the North American Multi-Model Ensemble (NMME) and a Distributed Time-Variant Gain Hydrological Model (DTVGM) was established and assessed over the upstream and midstream of Heihe River basin (UHRB and MHRB), a typical arid endorheic basin. The 3-month Standardized Precipitation Index (SPI3) and 1-month Standardized Streamflow Index (SSI1) were used to capture meteorological and hydrological drought, and values below −1 indicate drought events. The skill of the forecasting systems was evaluated in terms of anomaly correlation (AC) and Brier score (BS) or Brier skill score (BSS). The predictability for meteorological drought was quantified using AC and BS with a “perfect model” assumption, referring to the upper limit of forecast skill. The hydrological predictability was to distinguish the role of initial hydrological conditions (ICs) and meteorological forcings, which was quantified by root-mean-square error (RMSE) within the ESP (Ensemble Streamflow Prediction) and reverse ESP framework. The UHRB and MHRB showed season-dependent meteorological drought predictability and forecast skill, with higher values during winter and autumn than that during spring. For hydrological forecasts, the forecast skill in the UHRB was higher than that in MHRB. Predicting meteorological droughts more than 2 months in advance became difficult because of complex climate mechanisms. However, the hydrological drought forecasts could show some skills up to 3–6 lead months due to memory of ICs during cold and dry seasons. During wet seasons, there are no skillful hydrological predictions from lead month 2 onwards because of the dominant role of meteorological forcings. During spring, the improvement of hydrological drought predictions was the most significant as more streamflow was generated by seasonal snowmelt. Besides meteorological forcings and ICs, human activities have reduced the hydrological variability and increased hydrological drought predictability during the wet seasons in the MHRB.

scholarly journals Identifying a Transition Climate Zone in an Arid River Basin using a Hydrological Drought Index

2018 ◽  
Author(s):  
Libo Zhang ◽  
Yongqiang Liu ◽  
Lu Hao ◽  
Decheng Zhou ◽  
Cen Pan ◽  
...  
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Classification ◽  
Climate Zone ◽  
Annual Variability ◽  
Hydrological Drought Index

Abstract. Drought indices have been widely used in climate classification. However, there is not enough evidence for their ability in identifying the multiple climate types in areas with complex topography and landscape, especially in those areas with a transition climate. This study compares a meteorological drought index, the aridity index (AI) defined as the ratio of precipitation (P) to potential evapotranspiration (PET), with a hydrological drought index, the evaporative stress index (ESI) defined as the ratio of actual evapotranspiration (AET) to PET. We conducted this study using modeled high resolution climate data for period of 1980–2010 in the Heihe River Basin (HRB) in the arid northwestern China. PET was estimated using the Penman–Monteith and Hamon methods. The climate classified by AI shows two distinct climate types for the upper and the middle and lower basin reaches, while three types were found if ESI was used. This difference indicates that only ESI is able to identify a transition climate zone in the middle basin. This contrast between the two indices is also seen in the inter-annual variability and extreme dry/wet events. The magnitude of variability in the middle basin is close to that in the lower basin for AI, but different for ESI. AI has larger magnitude of the relative inter-annual variability and greater decreasing rate from 1980–2010 than ESI, suggesting the role of local hydrological processes in moderating extreme climate events. Thus, the hydrological drought index is better than the meteorological drought index for climate classification in the arid Heihe River Basin where local climate is largely determined by topography and landscape. We conclude that the land–surface processes and human disturbances play an important role in altering hydrological drought conditions and their spatial and temporal variability.

scholarly journals The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models

2018 ◽  
Vol 22 (9) ◽  
pp. 4649-4665 ◽  
Author(s):  
Anouk I. Gevaert ◽  
Ted I. E. Veldkamp ◽  
Philip J. Ward
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Propagation Time ◽  
Hydrological Models ◽  
Land Surface Models ◽  
Surface Models

Abstract. Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socioeconomic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices (SIs) of soil moisture, runoff, and streamflow from an ensemble of global hydrological models (GHMs) forced by a consistent meteorological dataset. Drought propagation is strongly related to climate types, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models (LSMs) than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 127 in situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 10 % of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.

scholarly journals Evolution characteristics and relationship of meteorological and hydrological droughts from 1961 to 2018 in Hanjiang River Basin, China

2021 ◽  
Author(s):  
Lin Wang ◽  
Jianyun Zhang ◽  
Amgad Elmahdi ◽  
Zhangkang Shu ◽  
Yinghui Wu ◽  
...  
Keyword(s):  
River Basin ◽  
Human Activities ◽  
Water Cycle ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Evolution Characteristics ◽  
Hanjiang River ◽  
Hydrological Droughts ◽  
Meteorological Droughts

Abstract In the context of global warming and increasing human activities, the acceleration of the water cycle will increase the risk of basin drought. In this study, to analyze the spatial and temporal evolution characteristics of hydrological and meteorological droughts over the Hanjiang River Basin (HRB); the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) were selected and applied for the period 1961–2018. In addition, the cross-wavelet method was used to discuss the relationship between hydrological drought and meteorological droughts. The results and analysis indicated that: (1) the meteorological drought in the HRB showed a complex cyclical change trend of flood-drought-flood from 1961 to 2018. The basin drought began to intensify from 1990s and eased in 2010s. The characteristics of drought evolution in various regions are different based on scale. (2) During the past 58 years, the hydrological drought in the HRB has shown a significant trend of intensification, particularly in autumn season. Also, the hydrological droughts had occurred frequently since the 1990s, and there were also regional differences in the evolution characteristics of drought in various regions. (3) Reservoir operation reduces the frequency of extreme hydrological drought events. The effect of reducing the duration and intensity of hydrological drought events by releasing water from the reservoir is most obvious at Huangjiagang Station, which is the nearest to Danjiangkou Reservoir. (4) The hydrological drought and meteorological drought in the HRB have the strongest correlation on the yearly scale. After 1990, severe human activities and climate change are not only reduced the correlation between hydrological drought and meteorological drought in the middle and lower reaches of the basin, but also reduced the lag time between them. Among them, the hydrological drought in the upper reaches of the basin lags behind the meteorological drought by 1 month, and the hydrological drought in the middle and lower reaches of the basin has changed from 2 months before 1990 to 1 month lagging after 1990.

scholarly journals The effect of climate on timescales of drought propagation in an ensemble of global hydrological models

2018 ◽  
Author(s):  
Anouk I. Gevaert ◽  
Ted I. E. Veldkamp ◽  
Philip J. Ward
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Propagation Time ◽  
Hydrological Models ◽  
Land Surface Models ◽  
Surface Models

Abstract. Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socio-economic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought, and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices of soil moisture, runoff, and streamflow from an ensemble of global hydrological models forced by a consistent meteorological dataset. Drought propagation is strongly related to climate, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 297 in-situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 20 % of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios.

scholarly journals Application of Meteorological and Hydrological Drought Indices to Establish Drought Classification Maps of the Ba River Basin in Vietnam

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 49 ◽  
Author(s):  
Doan Quang Tri ◽  
Tran Tho Dat ◽  
Dinh Duc Truong
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Assessment Tool ◽  
Swat Model ◽  
Standardized Precipitation Index ◽  
Aridity Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Calibration And Validation

The objective of this study was to establish drought classification maps to simulate and calculate the lack of discharge in the Ba River basin in Vietnam. The maps were established using three meteorological drought indices (the Standardized Precipitation Index (SPI), the Drought Index (J), and the Ped Index (Ped)), the Soil and Water Assessment Tool (SWAT) model, and the hydrological drought index (KDrought). The results from the calculation of the SPI, Aridity Index (AI), and Ped at three stations (An Khe, Ayunpa, and MDrak) showed that the J index was suitable for the study area. Based on the J index, an extreme drought was predicted to occur at the Ayunpa, An Khe, and MDrak stations. During the calibration process, the SWAT Calibration Uncertainties Program (SWAT-CUP) model, with automatic algorithms, was used to select the parameters to optimize the SWAT model. For the calibration and validation, the observed discharge at two hydrology stations, An Khe and Cung Son, from the periods 1981–1991 and 1992–2002, respectively, were used. The simulated discharge was found to be acceptable, with the Nash–Sutcliffe efficiency (NSE), Percent bias (PBIAS), and R2 reaching good levels in both calibration and validation. The results from the calculation of the drought index (KDrought), and the established drought classification maps in 2016, showed that the most affected areas were the communes of the Gia Lai and Dak Lak provinces. The results from the simulation and calculations were found to be consistent with the situation that occurred in practice. The application of meteorological and hydrological drought indices, as well as the hydrological model, to support impact assessments of drought classification in space and time, as well as the establishment of forecasting and warning maps, will help managers to effectively plan policy responses to drought.

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