scholarly journals Drought Monitoring Using Rainfall, Evapotranspiration and Streamflow Data: A Case Study of Kaduna River Catchment Area (Nigeria)

Author(s):  
A. Dare ◽  
E. J. Zakka ◽  
Maikano Samson ◽  
A. O. Afolabi ◽  
S. O. Okechalu ◽  
...  

Drought is defined as the lack of adequate precipitation, either rain or snow that causes reduced soil moisture or groundwater, diminished streamflow, crop damage and a general water shortage. The objective of this study focuses on meteorological and hydrological drought monitoring in river Kaduna catchment area. Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) drought indices were used to characterize meteorological drought while Streamflow Drought Index (SDI) was used for hydrological drought monitoring for a period of 34 years (1967 – 2001). DrinC software, a drought indices calculator, was used for the calculation of SPI, RDI, and SDI respectively. The drought severity classification based on meteorological and hydrological drought indices gave 33% and 37% drought conditions period with the year 1967 – 2001. Based on these indexes, the drought characteristics of the catchment area were investigated by analyzing meteorological data from 1967 to 2001. The results of this analysis show that more non-drought/normal conditions were predominant than drought conditions. During the period under study (34 years), only one-year return period of extreme drought condition.

2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su

<p>Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982–2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI<sub></sub>= 0.34, SSI<sub></sub>= 0.24, scPDSI<sub></sub>= 0.23, SPI<sub></sub>= 0.20, SPEI<sub></sub>= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982–1986, 1990–1996, and 2005–2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.</p>


2021 ◽  
Author(s):  
Oualid HAKAM ◽  
◽  
Abdennasser BAALI ◽  
Touria EL KAMEL ◽  
Ahouach Youssra ◽  
...  

Due to the lack of studies on drought in the Lower Sebou basin (LSB), the complexity of drought event and the difference in climate conditions. The identification of the most appropriate drought indices (DIs) to assess drought conditions has become a priority. Therefore, assessing the performance of different drought indices was considered in order to identify the universal drought indices that are well adapted to the LSB. Based on data availability, five DIs were used: Standardized Precipitation Index (SPI), Standardized Precipitation and Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI), self-calibrated Palmer Drought Severity Index (sc-PDSI) and Streamflow Drought Index (SDI). The DIs were calculated on an annual scale using monthly time series of precipitation, temperature and river flow from 1984-2016. Thornthwaite's method was used to calculate potential evapotranspiration (PET). Pearson's correlation (r) were analyzed. Furthermore, five decision criteria namely robustness, traceability, transparency, sophistication and scalability were used to evaluate the performance of these indices. The results proved the fact that SPI is suitable to detect the drought duration and intensity compared to other indices with high correlation coefficients especially in sub humid regions, knowing that it tends to give more results that are humid in stations with semi-arid climates. SPI, SPEI and RDI follow the same trend during the period studied. However, sc-PDSI appears to be the most sensitive to temperature and precipitation by overestimating the drought conditions. Eventually, the results of the performance evaluation criteria revealed that SPEI classified first (total score = 137) among other meteorological drought indices, followed by SPI, RDI and sc-PDSI.


2020 ◽  
Author(s):  
Jeongeun Won ◽  
Sangdan Kim

<p>In drought monitoring, it is very important to select climate variables to interpret drought. Most drought monitoring interprets drought as deficit in precipitation, so drought indices focused on the moisture supply side of the atmosphere have been mainly used. However, droughts can be caused not only by lack of rainfall, but also by various climate variables such as increase in temperature. In this regard, interest in potential evapotranspiration(PET), which is an moisture demand side of the atmosphere, is increasing and a PET-based drought index has been developed. However, complex droughts caused by various climate variables cannot be interpreted as a drought index that only considers precipitation or PET. In this study, we suggest a drought monitoring method that can reflect various future climate variables, including precipitation. In other words, copula-based joint drought index(CJDI), which incorporate standardized precipitation index(SPI) based on precipitation and evaporative demand drought index(EDDI) based on PET, is developed. CJDI, which considers both precipitation and PET, which are key variables related to drought, is able to properly monitor the drought events in Korea. In addition, future Drought severity – duration - frequency curves are derived to project future droughts compared to various drought indices. It is shown that CJDI can be used as a more reasonable drought index to establish the adaptation policy for future droughts by presenting the pattern of future droughts more realistically.</p><p><strong>Acknowledgment: </strong>This study was funded by the Korea Ministry of Environment (MOE) as Smart Urban Water Resources Management Program. (2019002950004)</p><p><strong>Keywords</strong>: Climate change; Copula; Drought; CJDI; Drought severity-duration-frequency curve</p>


Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.


2019 ◽  
Vol 43 (5) ◽  
pp. 627-642 ◽  
Author(s):  
Luis Eduardo Quesada-Hernández ◽  
Oscar David Calvo-Solano ◽  
Hugo G Hidalgo ◽  
Paula M Pérez-Briceño ◽  
Eric J Alfaro

The Central American Dry Corridor (CADC) is a sub-region in the isthmus that is relatively drier than the rest of the territory. Traditional delineations of the CADC’s boundaries start at the Pacific coast of southern Mexico, stretching south through Central America’s Pacific coast down to northwestern Costa Rica (Guanacaste province). Using drought indices (Standardized Precipitation Index, Modified Rainfall Anomaly Index, Palmer Drought Severity Index, Palmer Hydrological Drought Index, Palmer Drought Z-Index and the Reconnaissance Drought Index) along with a definition of aridity as the ratio of potential evapotranspiration (representing demand of water from the atmosphere) over precipitation (representing the supply of water), we proposed a CADC delineation that changes for normal, dry and wet years. The identification of areas that change their classification during extremely dry conditions is important because these areas may indicate the location of future expansion of aridity associated with climate change. In the same way, the delineation of the CADC during wet extremes allows the identification of locations that remain part of the CADC even during the wettest years and that may require special attention from the authorities.


2019 ◽  
Vol 11 (23) ◽  
pp. 2742 ◽  
Author(s):  
Tran ◽  
Tran ◽  
Myint ◽  
Latorre-Carmona ◽  
Ho ◽  
...  

Drought is a major natural disaster that creates a negative impact on socio-economic development and environment. Drought indices are typically applied to characterize drought events in a meaningful way. This study aims at examining variations in agricultural drought severity based on the relationship between standardized ratio of actual and potential evapotranspiration (ET and PET), enhanced vegetation index (EVI), and land surface temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A new drought index, called the enhanced drought severity index (EDSI), was developed by applying spatiotemporal regression methods and time-series biophysical data derived from remote sensing. In addition, time-series trend analysis in the 2001–2018 period, along with the Mann–Kendal (MK) significance test and the Theil Sen (TS) slope, were used to examine the spatiotemporal dynamics of environmental parameters (i.e., LST, EVI, ET, and PET), and geographically weighted regression (GWR) was subsequently applied in order to analyze the local correlations among them. Results showed that a significant correlation was discovered among LST, EVI, ET, and PET, as well as their standardized ratios (|r| > 0.8, p < 0.01). Additionally, a high performance of the new developed drought index, showing a strong correlation between EDSI and meteorological drought indices (i.e., standardized precipitation index (SPI) or the reconnaissance drought index (RDI)), measured at meteorological stations, giving r > 0.7 and a statistical significance p < 0.01. Besides, it was found that the temporal tendency of this phenomenon was the increase in intensity of drought, and that coastal areas in the study area were more vulnerable to this phenomenon. This study demonstrates the effectiveness of EDSI and the potential application of integrating spatial regression and time-series data for assessing regional drought conditions.


2021 ◽  
Vol 13 (4) ◽  
pp. 2066
Author(s):  
Jin Hyuck Kim ◽  
Jang Hyun Sung ◽  
Eun-Sung Chung ◽  
Sang Ug Kim ◽  
Minwoo Son ◽  
...  

Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.


Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 49 ◽  
Author(s):  
Doan Quang Tri ◽  
Tran Tho Dat ◽  
Dinh Duc Truong

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.


2021 ◽  
Vol 21 (4) ◽  
pp. 1323-1335
Author(s):  
Zheng Liang ◽  
Xiaoling Su ◽  
Kai Feng

Abstract. Monitoring drought and mastering the laws of drought propagation are the basis for regional drought prevention and resistance. Multivariate drought indicators considering meteorological, agricultural and hydrological information may fully describe drought conditions. However, series of hydrological variables in cold and arid regions that are too short or missing make it difficult to monitor drought. This paper proposed a method combining Soil and Water Assessment Tool (SWAT) and empirical Kendall distribution function (KC′) for drought monitoring. The SWAT model, based on the principle of runoff formation, was used to simulate the hydrological variables of the drought evolution process. Three univariate drought indexes, namely meteorological drought (standardized precipitation evapotranspiration index; SPEI), agricultural drought (standardized soil moisture index; SSI) and hydrological drought (standardized streamflow drought index; SDI), were constructed using a parametric or non-parametric method to analyze the propagation time from meteorological drought to agricultural drought and hydrological drought. The KC′ was used to build a multivariable comprehensive meteorology–agriculture–hydrology drought index (MAHDI) that integrated meteorological, agricultural and hydrological drought to analyze the characteristics of a comprehensive drought evolution. The Jinta River in the inland basin of northwestern China was used as the study area. The results showed that agricultural and hydrological drought had a seasonal lag time from meteorological drought. The degree of drought in this basin was high in the northern and low in the southern regions. MAHDI proved to be acceptable in that it was consistent with historical drought records, could catch drought conditions characterized by univariate drought indexes, and capture the occurrence and end of droughts. Nevertheless, its ability to characterize mild and moderate droughts was stronger than severe droughts. In addition, the comprehensive drought conditions showed insignificant aggravating trends in spring and summer and showed insignificant alleviating trends in autumn and winter and at annual scales. The results provided theoretical support for the drought monitoring in the Jinta River basin. This method provided the possibility for drought monitoring in other watersheds lacking measured data.


2021 ◽  
Author(s):  
Uttam Singh ◽  
Pooja Agarwal ◽  
Pramod Kumar Sharma

Abstract Climate change is adversely affecting the development, management, and planning of surface and groundwater resources. The meteorological drought becomes a severe natural problem, and it can occur in any climatic region of the world. So, monitoring and minimizing drought is a crucial stage for analyzing and predicting drought impacts. A single drought index can't assess each aspect of the meteorological drought. In this study, we considered seven drought indices such as the Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Percent Normal drought index (PNI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-score index (ZSI). The drought was analyzed for 3, 6, 9, and 12 months’ time-step, and drought classification and threshold values were estimated. SPI showed maximum correlation values 0.389, 0.412, 0.560,and 0.996 for 3, 6, 9,and 12-month time steps compared to the other drought indices. The value of correlation is increased with the increase in time step for all drought indices; therefore, the accuracy of drought assessment also increases with an increase in time step. The Mann-Kendall's trend test was analyzed at a 5% level of significance for drought assessments. The drought magnitude and severity of the Betwa river basin were estimated based on the meteorological data (Rainfall) for the year between 1970 to 2014.


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