Analyzing Resilience and Food Insecurity of Drought Prone Communities of Tharparkar Desert, Pakistan

Shahzad, Laila; Yasin, Asma; liaqat, ammar; Mansoor, Asma; Sharif, Faiza; raiz, umair

doi:10.21203/rs.3.rs-472894/v1

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Communities that rely on Pakistan's natural resources are especially at risk. The climate is hot, arid, and prone to drought and the rainfall is less than 200 millimetres per year [24]. Extremes characterize the Thar Desert.…”

Section: Study Areamentioning

confidence: 99%

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Meteorological drought mitigation for combating climate change: a case study of southern Sindh, Pakistan

Kumar

Shah

Khokhar

et al. 2023

Mehran Univ. res. j. eng. technol.

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A meteorological drought study is performed using monthly time scale data from three separate locations in southern Sindh, Pakistan. Rainfall and temperature have been used to identify the drought. These data were transformed into drought indices known as the standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI), which were derived using (the Hargreaves equation). In this study, two indices are compared for three separate meteorological stations Chhor, Mithi, and Badin where most socioeconomic livelihoods depend heavily on water. The SPEI is produced through a simple water balance combining precipitation and temperature, in distinction to the SPI, it just considers precipitation. In conclusion, our study showed that both indices were capable of detecting droughts that fluctuated in time across the reference period of 2004–2021. SPI and SPEI's direction of change was similar, however the impact on the drought condition varied. SPEI discovered more droughts with longer durations and greater with 13 moderate droughts at SPEI-3 for Chhor and Badin Station while Mithi indicated 8 moderate droughts during 2004-2021 and SPI-3 indicated 4 moderates for Chhor, Mithi and Badin indicated 6 moderate drought. Conversely, SPEI discovered more moderate-level droughts than SPI, however they were of shorter length and less frequent occurrence than the severe to moderate droughts. The findings imply that drought characteristics are significantly influenced by temperature variability.

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Section: Study Areamentioning

confidence: 99%

“…SPI and SPEI drought classification by [9]. [23][24][25][26][27][28][29][30][31]. Due to its ability to be calculated over several reference periods and to account for the different response times of typical hydrological parameters to rainfall, SPI equation 7 is frequently used to evaluate drought.…”

Section: Tablementioning

confidence: 99%

Meteorological drought mitigation for combating climate change: a case study of southern Sindh, Pakistan

Kumar

Shah

Khokhar

et al. 2023

Mehran Univ. res. j. eng. technol.

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Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan

et al. 2021

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Demand for water resources has increased dramatically due to the global increase in consumption of water, which has resulted in water depletion. Additionally, global climate change has further resulted as an impediment to human survival. Moreover, Pakistan is among the countries that have already crossed the water scarcity line, experiencing drought in the water-stressed Thar desert. Drought mitigation actions can be effectively achieved by forecasting techniques. This research describes the application of a linear stochastic model, i.e., Autoregressive Integrated Moving Average (ARIMA), to predict the drought pattern. The Standardized Precipitation Evapotranspiration Index (SPEI) is calculated to develop ARIMA models to forecast drought in a hyper-arid environment. In this study, drought forecast is demonstrated by results achieved from ARIMA models for various time periods. Result shows that the values of p, d, and q (non-seasonal model parameter) and P, D, and Q (seasonal model parameter) for the same SPEI period in the proposed models are analogous where “p” is the order of autoregressive lags, q is the order of moving average lags and d is the order of integration. Additionally, these parameters show the strong likeness for Moving Average (M.A) and Autoregressive (A.R) parameter values. From the various developed models for the Thar region, it has been concluded that the model (0,1,0)(1,0,2) is the best ARIMA model at 24 SPEI and could be considered as a generalized model. In the (0,1,0) model, the A.R term is 0, the difference/order of integration is 1 and the moving average is 0, and in the model (1,0,2) whose A.R has the 1st lag, the difference/order of integration is 0 and the moving average has 2 lags. Larger values for R2 greater than 0.9 and smaller values of Mean Error (ME), Mean Absolute Error (MAE), Mean Percentile Error (MPE), Mean Absolute Percentile Error (MAPE), and Mean Absolute Square Error (MASE) provide the acceptance of the generalized model. Consequently, this research suggests that drought forecasting can be effectively fulfilled by using ARIMA models, which can be assist policy planners of water resources to place safeguards keeping in view the future severity of the drought.

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Prevalence, Trends, and Socioeconomic Determinants of Coexisting Forms of Malnutrition Amongst Children under Five Years of Age in Pakistan

et al. 2021

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In Pakistan, malnutrition is a chronic issue. Concerns regarding coexisting forms of malnutrition (CFM) in an individual child are emerging, as children suffering from CFM have a 4 to 12-fold higher risk of death compared with healthy children. This study assessed the prevalence, trends, and socioeconomic determinants of various types of CFM using Pakistan Demographic and Health Survey (PDHS) datasets. Data from children aged 0–5 years old, with complete height and weight information, and valid anthropometry, from all regions of Pakistan (except residents of Azad Jammu Kashmir (AJK) and Federally Administered Tribal Areas (FATA), and non-de jure residents), were included. The prevalence of CFM was 30.6% in 2012–2013 and 21.5% in 2017–2018 PDHS. Both PDHSs reported a significantly higher prevalence of CFM in Sindh and Baluchistan compared with other regions of Pakistan. Improved socioeconomic status significantly reduced the odds of various types of CFM, except the coexistence of underweight with wasting. The high prevalence of CFM in Pakistan can be averted by multisectoral collaboration and by integrating nutrition-sensitive and nutrition-specific interventions.

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Analyzing Resilience and Food Insecurity of Drought Prone Communities of Tharparkar Desert, Pakistan

Cited by 3 publications

References 19 publications

Meteorological drought mitigation for combating climate change: a case study of southern Sindh, Pakistan

Meteorological drought mitigation for combating climate change: a case study of southern Sindh, Pakistan

Forecasting of Drought: A Case Study of Water-Stressed Region of Pakistan

Prevalence, Trends, and Socioeconomic Determinants of Coexisting Forms of Malnutrition Amongst Children under Five Years of Age in Pakistan

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