scholarly journals Lag in Hydrologic Recovery Following Extreme Meteorological Drought Events: Implications for Ecological Water Requirements

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 837 ◽  
Author(s):  
Qiang Liu ◽  
Xiaojing Ma ◽  
Sirui Yan ◽  
Liqiao Liang ◽  
Jihua Pan ◽  
...  
Keyword(s):  
Time Lag ◽  
Meteorological Drought ◽  
Environmental Flow ◽  
Vital Role ◽  
Hydrological Drought ◽  
Habitat Recovery ◽  
Abrupt Changes ◽  
Identification Technique ◽  
Recession Constant ◽  
Hydrological Regimes

Hydrological regimes, being strongly impacted by climate change, play a vital role in maintaining the integrity of aquatic river habitats. We investigated lag in hydrologic recovery following extreme meteorological drought events, and we also discussed its implications in the assessment of ecological environment flow. We used monthly anomalies of three specific hydrometeorological variables (precipitation, streamflow, and baseflow) to identify drought, while we used the Chapman–Maxwell method (the CM filter) with recession constant calculated from Automatic Baseflow Identification Technique (ABIT) to separate baseflow. Results showed that: (i) Compared to the default recession parameter (α = 0.925), the CM filter with the ABIT estimate (α = 0.984) separated baseflow more accurately. (ii) Hydrological drought, resulting from meteorological drought, reflected the duration and intensity of meteorological drought; namely, longer meteorological drought periods resulted in longer hydrological drought periods. Interestingly, the time lag in streamflow and baseflow indicated that aquatic ecosystem habitat recovery also lagged behind meteorological drought. (iii) Assessing environmental flow by quantifying drought provided greater detail on hydrological regimes compared to abrupt changes, such as the increased hydrological periods and the different environment flows obtained. Taken together, our results indicated that the hydrological response in streamflow and baseflow (e.g., the time lag and the precipitation recovery rate (Pr)) played a vital role in the assessment of environmental flow.

scholarly journals Prediction of Multi-Scalar Standardized Precipitation Index by Using Artificial Intelligence and Regression Models

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Anurag Malik ◽  
Anil Kumar ◽  
Priya Rai ◽  
Alban Kuriqi
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Inference ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Vital Role ◽  
Precipitation Index ◽  
Visual Interpretation ◽  
Inference System ◽  
Drought Prediction ◽  
Optimal Functioning

Accurate monitoring and forecasting of drought are crucial. They play a vital role in the optimal functioning of irrigation systems, risk management, drought readiness, and alleviation. In this work, Artificial Intelligence (AI) models, comprising Multi-layer Perceptron Neural Network (MLPNN) and Co-Active Neuro-Fuzzy Inference System (CANFIS), and regression, model including Multiple Linear Regression (MLR), were investigated for multi-scalar Standardized Precipitation Index (SPI) prediction in the Garhwal region of Uttarakhand State, India. The SPI was computed on six different scales, i.e., 1-, 3-, 6-, 9-, 12-, and 24-month, by deploying monthly rainfall information of available years. The significant lags as inputs for the MLPNN, CANFIS, and MLR models were obtained by utilizing Partial Autocorrelation Function (PACF) with a significant level equal to 5% for SPI-1, SPI-3, SPI-6, SPI-9, SPI-12, and SPI-24. The predicted multi-scalar SPI values utilizing the MLPNN, CANFIS, and MLR models were compared with calculated SPI of multi-time scales through different performance evaluation indicators and visual interpretation. The appraisals of results indicated that CANFIS performance was more reliable for drought prediction at Dehradun (3-, 6-, 9-, and 12-month scales), Chamoli and Tehri Garhwal (1-, 3-, 6-, 9-, and 12-month scales), Haridwar and Pauri Garhwal (1-, 3-, 6-, and 9-month scales), Rudraprayag (1-, 3-, and 6-month scales), and Uttarkashi (3-month scale) stations. The MLPNN model was best at Dehradun (1- and 24- month scales), Tehri Garhwal and Chamoli (24-month scale), Haridwar (12- and 24-month scales), Pauri Garhwal (12-month scale), Rudraprayag (9-, 12-, and 24-month), and Uttarkashi (1- and 6-month scales) stations, while the MLR model was found to be optimal at Pauri Garhwal (24-month scale) and Uttarkashi (9-, 12-, and 24-month scales) stations. Furthermore, the modeling approach can foster a straightforward and trustworthy expert intelligent mechanism for projecting multi-scalar SPI and decision making for remedial arrangements to tackle meteorological drought at the stations under study.

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 Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products

2018 ◽  
Vol 22 (9) ◽  
pp. 5041-5056 ◽  
Author(s):  
José Miguel Delgado ◽  
Sebastian Voss ◽  
Gerd Bürger ◽  
Klaus Vormoor ◽  
Aline Murawski ◽  
...  
Keyword(s):  
Rainy Season ◽  
Meteorological Drought ◽  
Skill Score ◽  
Hydrological Drought ◽  
Northeastern Brazil ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.

scholarly journals Drought Propagation Patterns under Naturalized Condition Using Daily Hydrometeorological Data

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jianzhu Li ◽  
Yuangang Guo ◽  
Yixuan Wang ◽  
Shanlong Lu ◽  
Xu Chen
Keyword(s):  
Early Warning ◽  
Assessment Tool ◽  
Swat Model ◽  
Meteorological Drought ◽  
Threshold Level ◽  
Hydrological Drought ◽  
Propagation Pattern ◽  
Drought Early Warning ◽  
Hydrological Droughts

Drought propagation pattern forms a basis for establishing drought monitoring and early warning. Due to its regional disparity, it is necessary and significant to investigate the pattern of drought propagation in a specific region. With the objective of improving understanding of drought propagation pattern in the Luanhe River basin, we first simulated soil moisture and streamflow in naturalized situation on daily time scale by using the Soil and Water Assessment Tool (SWAT) model. The threshold level method was utilized in identifying drought events and drought characteristics. Compared with meteorological drought, the number of drought events was less and duration was longer for agricultural and hydrological droughts. The results showed that there were 3 types of drought propagation pattern: from meteorological drought to agricultural/hydrological drought (M-A/H), agricultural/hydrological drought without meteorological drought (NM-A/H), and meteorological drought only (M). To explain the drought propagation pattern, possible driven factors were determined, and the relations between agricultural/hydrological drought and the driven factors were built using multiple regression models with the coefficients of determination of 0.4 and 0.656, respectively. These results could provide valuable information for drought early warning and forecast.

scholarly journals Monitoring Droughts in the Greater Changbai Mountains Using Multiple Remote Sensing-Based Drought Indices

2020 ◽  
Vol 12 (3) ◽  
pp. 530 ◽  
Author(s):  
Yang Han ◽  
Ziying Li ◽  
Chang Huang ◽  
Yuyu Zhou ◽  
Shengwei Zong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Lag ◽  
Remote Sensing Data ◽  
Meteorological Drought ◽  
Condition Index ◽  
Temporal Variations ◽  
Changbai Mountains ◽  
Drought Indices ◽  
Drought Condition ◽  
Meteorological Observations

Various drought indices have been developed to monitor drought conditions. Each index has typical characteristics that make it applicable to a specific environment. In this study, six popular drought indices, namely, precipitation condition index (PCI), temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), scaled drought condition index (SDCI), and temperature–vegetation dryness index (TVDI), have been used to monitor droughts in the Greater Changbai Mountains(GCM) in recent years. The spatial pattern and temporal trend of droughts in this area in the period 2001–2018 were explored by calculating these indices from multi-source remote sensing data. Significant spatial–temporal variations were identified. The results of a slope analysis along with the F-statistic test showed that up to 20% of the study area showed a significant increasing or decreasing trend in drought. It was found that some drought indices cannot be explained by meteorological observations because of the time lag between meteorological drought and vegetation response. The drought condition and its changing pattern differ from various land cover types and indices, but the relative drought situation of different landforms is consistent among all indices. This work provides a basic reference for reasonably choosing drought indices for monitoring drought in the GCM to gain a better understanding of the ecosystem conditions and environment.

scholarly journals Impact of Meteorological Drought in Upper Blue Nile Basin on the Hydrological Drought of Nile River in Egypt

2020 ◽  
Vol 9 (6) ◽  
pp. 50-55
Keyword(s):  
Water Resources ◽  
Pearson Correlation ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Nile River ◽  
Nile Basin ◽  
Blue Nile ◽  
Blue Nile Basin ◽  
Upper Blue Nile Basin

Precipitation over the Upper Blue Nile Basin in Ethiopia contributes with 85% of the Nile river which provides 93% of Egypt’s conventional water resources. This study aims at assessing the meteorological drought in different locations in the Upper Blue Nile Basin and their relationship with the hydrological drought of Nile river in Egypt. The metrological drought was calculated by the Standard Precipitation Index (SPI) at five stations inside and close to the Upper Blue Nile Basin in Ethiopia, whereas the hydrological drought was calculated by the Streamflow Drought Index (SDI) at Dongola station at Nasser lake entrance. Both indices were calculated using the Drought Indices Calculator (DrinC) software. The selected study period was from 1973 to 2017 based on the availability of recorded data for meteorological stations in Ethiopia, and the streamflow for Dongola station. The data was categorized for each station by considering time periods of 1, 3, 6, 9, and 12 months based on their homogeneity. The correlation between SPI and SDI was evaluated using the Pearson correlation coefficient. The results showed a correlation between SPI for the five stations in the Upper Blue Nile Basin and SDI for Dongola station, where Gore station represented the highest frequency of significance at different time scales especially at the 3-months’ scale. The results confirm the relationship between SPI at Gore Station and SDI at Dongola Station, which means that the hydrological drought in Egypt is highly affected by the meteorological drought in the area surrounding Gore station. The paper recommends improving techniques for monitoring and overseeing drought hazards and assessing more meteorological stations to accurately predict climate change variations in Upper Blue Nile Basin and its effect on Egypt’s water resources.

scholarly journals The Influence of a Prolonged Meteorological Drought on the Catchment Water Storage Capacity: A Hydrological Model Perspective

2020 ◽  
Author(s):  
Zhengke Pan ◽  
Pan Liu ◽  
Chongyu Xu ◽  
Lei Cheng ◽  
Jing Tian ◽  
...  
Keyword(s):  
Change Point ◽  
Storage Capacity ◽  
Critical Role ◽  
Time Lag ◽  
Water Storage ◽  
Meteorological Drought ◽  
Change Point Analysis ◽  
Runoff Generation ◽  
Broadleaf Forest ◽  
Water Storage Capacity

Abstract. Understanding the propagation process of prolonged meteorological droughts (i.e., decade) helps solve the problem of increasing water scarcity around the world. Historical literature studied the propagation between different drought types (e.g., from meteorological to hydrological drought) with mainly statistical approaches, however, little attention has been paid to the causality between the meteorological drought with potential changes in the Catchment Water Storage Capacity (CWSC) where the latter plays a critical role in catchment response behavior to former. This study used the temporal variation in the estimated value of a model parameter that denotes the CWSC in its model structure to reflect the potential changes in real CWSC. The most likely Change points of the CWSC were determined based on the Bayesian Change point analysis. Also, the possible association and linkage between the shift in the CWSC and the time-lag of the catchment (i.e., time-lag between the occurrence of the drought with the Change point) with multiple catchment properties and climate characteristics have been studied. Catchments from southeastern Australia were used as a study area to verify the effectiveness of the proposed approach. Results indicated that (1) in 62.7 % of the catchments, the sustained drought causes significant shifts in the CWSC. The shift led to the opposite response in two subsets of catchments, i.e., 48.2 % of catchments had lower runoff generation rates for a given rainfall while 14.5 % of catchments had higher runoff generation rate. (2) Catchments with larger elevation and slope, lower forest coverage of Evergreen Broadleaf Forest are more likely to have increase in the CWSC during a chronic drought while smaller catchments with lower elevation, lower coverage of the Evergreen Broadleaf Forest are more likely to have a decrease in the CWSC. (3) The changed catchments were not equally susceptible to the pressure due to persistent meteorological drought. Catchments with a lower proportion of Evergreen Broadleaf Forest usually have longer time-lag and are more resilient. This study improves our understanding of possible changes in CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system.

scholarly journals Analysing 21st century meteorological and hydrological drought events in Slovakia

2018 ◽  
Vol 66 (4) ◽  
pp. 393-403 ◽  
Author(s):  
Miriam Fendeková ◽  
Tobias Gauster ◽  
Lívia Labudová ◽  
Dana Vrablíková ◽  
Zuzana Danáčová ◽  
...  
Keyword(s):  
Water Balance ◽  
Extreme Values ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
River Basins ◽  
Hydrological Drought ◽  
Water Balance Components ◽  
Extreme Values Distribution ◽  
The Standardized Precipitation Index ◽  
The Relationship

Abstract Several quite severe droughts occurred in Europe in the 21st century; three of them (2003, 2012 and 2015) hit also Slovakia. The Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration Index (SPEI) were used for assessment of meteorological drought occurrence. The research was established on discharge time series representing twelve river basins in Slovakia within the period 1981–2015. Sequent Peak Algorithm method based on fixed threshold, three parametric Weibull and generalized extreme values distribution GEV, factor and multiple regression analyses were employed to evaluate occurrence and parameters of hydrological drought in 2003, 2011–2012 and 2015, and the relationship among the water balance components. Results showed that drought parameters in evaluated river basins of Slovakia differed in respective years, most of the basins suffered more by 2003 and 2012 drought than by the 2015 one. Water balance components analysis for the entire period 1931–2016 showed that because of continuously increasing air temperature and balance evapotranspiration there is a decrease of runoff in the Slovak territory.

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