Rainfall Analysis for Hyderabad and Nawabshah, Sindh, Pakistan

Mahessar, A. A.; Qureshi, Abdul Latif; Sadiqui, B.; Kori, S. M.; Mukwana, Kishan Chand; Qureshi, Abdul Sami; Leghari, K. Q.

doi:10.48084/etasr.3923

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…Learning about climatic behavior in a region improves hydraulic constructions and plays a critical part in the management of water resources in various term lengths [1]. Researchers are trying to answer questions such as if there is there a climate change in the study region and how can the existence of any change be confirmed.…”

Section: Introductionmentioning

confidence: 99%

A Spatiotemporal Approach in Detecting and Analyzing Hydro-climatic Change in Northwest Algeria

Bouraoui

Medjerab

2022

Eng. Technol. Appl. Sci. Res.

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Understanding climatic behavior, particularly that of semi-arid regions, is essential in order to optimize water resources management and provide protection from climatic risks. Water resources have great socio-economic and environmental importance. This paper focuses on the statistical analysis of the rainfall regime of northwest Algeria and estimates its spatial distribution and temporal variation. To this end, time series and principal component analysis were performed on rainfall series recorded from 1913 to 2009, representing the annual precipitation from thirty meteorological stations to discover patterns and trends in the studied region. Furthermore, the applied spectral analysis of the time series reveals the existence of a period of approximately 97 years at all stations. ArcGIS along with statistical and analytical tools like SPSS and XLSTAT were utilized in this study of the climatic behavior in northwest Algeria.

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Section: Introductionmentioning

confidence: 99%

A Spatiotemporal Approach in Detecting and Analyzing Hydro-climatic Change in Northwest Algeria

Bouraoui

Medjerab

2022

Eng. Technol. Appl. Sci. Res.

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Comparative Analysis of LSTM, BILSTM and ARIMA for Time Series Forecasting on 116 years of Temperature and Rainfall Data from Pakistan

2023

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Numerous aspects of human life, including agriculture, transportation, and health, are significantly influenced by weather, both economically and socially. Rain has an impact on landslides, floods, and other natural disasters. We are motivated to create a model for comprehending and forecasting rain in order to provide advanced warning in a spectrum of areas such as transport, agriculture, and so on because of the numerous consequences that rain and temperature have on human survival. In this study, a dataset for temperature and rainfall for Pakistan for 116 years is used. Comparative analysis of ARIMA, LSTM and BILSTM is performed. For this study, 90% of data is used for training and the 10% for testing. Normalization is also performed to clean data. According to the results, LSTM and BILSTM are better than ARIMA but for specific cases of rainfall, BILSTM performed better than LSTM and for Temperature LSTM outperformed BILSTM.

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An Evaluation of the Extreme Rainfall Event of 2010 over the Kabul River Basin using the WRF Model

Rafi

Dars

Strong

et al. 2022

Eng. Technol. Appl. Sci. Res.

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Extreme precipitation events are among the most severe weather hazards. Knowledge about the spatial patterns underlying such events in the Upper Indus Basin is limited because estimating precipitation is very challenging due to the data scarcity and the complex orography. Numerical weather prediction models can be applied at a fine resolution to overcome this issue. The Advanced Research Weather Research and Forecasting (WRF) model version 3.8.1 was applied over the Kabul River Basin to simulate the temperature and precipitation of monsoon season 2010, i.e., 1st May to 16th September 2010. We considered the May month as a spin-up period. The initial and boundary conditions were derived from the National Oceanic and Atmospheric Administration, Climate Forecast System Reanalysis data. The model was set up by using two-nested domains with increasing horizontal resolution moving inward from 15km on domain d01 to 5km on domain d02. The simulations were compared with TRMM 3B42, and station data collected from the Pakistan Meteorological Department and Water and the Power Development Authority using bias, percentage bias, root mean square error, and Pearson correlation. The results revealed that the simulated precipitation was improved from d01 to d02. However, the model showed mixed results with overestimation of precipitation at some stations and underestimations at others. Simulated precipitation generally agreed better with TRMM than with station data. Overall, the results indicate that the WRF model can be used to simulate heavy precipitation in complex terrain.

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Rainfall Analysis for Hyderabad and Nawabshah, Sindh, Pakistan

Cited by 4 publications

References 6 publications

A Spatiotemporal Approach in Detecting and Analyzing Hydro-climatic Change in Northwest Algeria

A Spatiotemporal Approach in Detecting and Analyzing Hydro-climatic Change in Northwest Algeria

Comparative Analysis of LSTM, BILSTM and ARIMA for Time Series Forecasting on 116 years of Temperature and Rainfall Data from Pakistan

An Evaluation of the Extreme Rainfall Event of 2010 over the Kabul River Basin using the WRF Model

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