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Publications (68)
Understanding the changing characteristics of climatic water balance (CWB) in arid regions is essential for assessing the impacts of climate change on water resource availability. This study investigates the spatiotemporal patterns of CWB on monthly, annual, and seasonal (monsoon and winter) timescales for the period 1961–2016 in the Balochistan pr...
Drought is one of the significant natural disasters that has a profound impact on human societies, particularly in arid places such as Balochistan, Pakistan. Geographic information system and remote sensing has played a major role in predicting the effect of drought events and mitigate. Therefore, the purpose of this study was firstly to evaluate t...
Changes in precipitation and temperature have crucial implications in the arid region due to their fragile environment. This study was an attempt to estimate possible spatiotemporal alteration of annual and seasonal precipitation and temperature in Iraq. Statistical downscaling of Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate...
Satellite-based precipitation (SBP) is emerging as a reliable source for high-resolution rainfall estimates over the globe. However, uncertainty in SBP is still significant, limiting their use without evaluation and often without bias correction. The bias correction of SBP remains a challenge for atmospheric scientists. The present study evaluated...
Satellite-based precipitation (SBP) is emerging as a reliable source for high-resolution rainfall estimates over the globe. However, uncertainty in SBP is still significant, limiting their use without evaluation and often without bias correction. The bias correction of SBP remained a challenge for atmospheric scientists. In this study, the performa...
This study presents an efficient approach to predict the Rabi and Kharif crop yield using a relatively new and robust machine learning (ML) model named random forest (RF). The standard precipitation evaporation index (SPEI) with different time lags (e.g., 1 to 12 months) are utilized as predictive variables. The SPEI was estimated using the climate...
The main goal of this research is to develop a 3D groundwater (GW) model using MODFLOW software to assess the potential effect of increasing pumping discharges on GW level in the Nile Delta Aquifer (NDA). In this study, the current state of the irrigation canals and GW recharge are considered in the GW model. The simulated GW level was compared wit...
Reliable precipitation data are often required for conducting hydro-climatological assessments. Therefore, the study aims to detect the inhomogeneity in each calendar month, mean annual and monthly time series precipitation data of Balochistan, an arid province of Pakistan. The inhomogeneity was assessed using standard normal homogeneity test, Buis...
Accurate representation of precipitation over time and space is vital for hydro-climatic studies. Appropriate selection of gridded precipitation data (GPD) is important for regions where long-term in situ records are unavailable and gauging stations are sparse. This study was an attempt to identify the best GPD for the data-poor Amu Darya River bas...
In recent years, the use of Gravity Recovery and Climate Experiment (GRACE) data has emerged as a valuable tool for investigating groundwater resources in data-scarce regions. This chapter reports on a study carried out to investigate and understand trends in the spatial variability of groundwater storage of Pakistan. We used three sets of GRACE da...
An approach is proposed in the present study to estimate the soil erosion in data-scarce Kokcha subbasin in Afghanistan. The Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The satellite-based data are used to obtain the RUSLE factors. The results show that the slight (71.34%) and moderate (25.46%) erosion are d...
Global climate models (GCMs) of Coupled Model Intercomparison Project 6 (CMIP6) has designed with new socioeconomic pathway scenarios to incorporate the socioeconomic changes along with greenhouse gas emissions to project future climate. Performance of 35 GCMs of CMIP6 was evaluated in this study in replicating APHRODITE rainfall in the Mainland So...
Modelling the probable effect of global warming on precipitation over the northern sub-Himalayan region is very important to ensure sustainable water supply for Pakistan. The aim of the study is to develop statistical downscaling models for the projection of precipitation using the outputs of Coupled Model Intercomparison Project Phase 5 global cir...
Knowledge of the variability and the changes in potential evapotranspiration (PET) is imperative for agriculture and water resource planning and management. There is a growing concern on alteration of PET because of global climate change. The spatial patterns of the changes in PET for annual and two key cropping seasons of Pakistan namely, Kharif a...
Like many other African countries, incidence of drought is increasing in Nigeria. In this work, spatiotemporal changes in droughts under different representative concentration pathway (RCP) scenarios were assessed; considering their greatest impacts on life and livelihoods in Nigeria, especially when droughts coincide with the growing seasons. Thre...
The Palmers’ crop moisture index (CMI) was used to assess the changing pattern of crop water stress of Bangladesh. Daily rainfall and temperature data for the period 1961–2010 recorded at eleven meteorological stations distributed across the country were used to estimate the time series of CMI. The run theory was used to estimate a set of metrics f...
A multiple variable bias correction approach has been proposed for the projection of the changes in spatial and temporal pattern of rainfall in Borneo Island due to climate change. The ensemble of General Circulation Models (GCMs) was selected through the combination of past performance and envelope approaches. The selected GCMs were downscaled usi...
The selection of global climate models (GCMs) for a region remained a difficult step in climate change studies. A state-of-the-art Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm is proposed in this paper for GCM selection. The ranking of GCMs obtained using SVM-RFE was compared to that obtained using entropy-based similari...
Multi-Model Ensembles (MMEs) are often employed to reduce the uncertainties related to GCM simulations/projections. The objective of this study was to evaluate the performance of MMEs developed using machine learning (ML) algorithms with different combinations of GCMs ranked based on their performance and determine the optimum number of GCMs to be...
Expansion of arid lands due to climate change, particularly in water stressed regions of the world can have severe implications on the economy and people's livelihoods. The spatiotemporal trends in aridity, the shift of land from lower to higher arid classes and the effect of this shift on different land uses in Syria have been evaluated in this st...
The climate modelling community has trialled a large number of metrics for evaluating the temporal performance of general circulation models (GCMs), while very little attention has been given to the assessment of their spatial performance, which is equally important. This study evaluated the performance of 36 Coupled Model Intercomparison Project 5...
Water is gradually becoming scarce in Afghanistan like in many other regions of the globe. The objective of this study was to evaluate the spatial changes in the availability and sustainability of water resources in Afghanistan. The Terrestrial Water Storage (TWS) data of the Gravity Recovery and Climate Experiment (GRACE) satellite obtained from t...
Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensi...
Among the regression techniques used in building statistical downscaling models, genetic programming (GP) which mimics Darwin's theory of biological evolution possesses several pros such as it evolves explicit linear or non-linear relationships while identifying optimum predictors, and it discards irrelevant and redundant information in predictors....
This study uses a multi-model ensemble (MME) for the assessment of the spatial and temporal variations of rainfall in peninsular Malaysia under climate change scenarios. The past performance approach was used for the selection of GCM ensemble from a pool of Coupled Model Intercomparison Project Phase 5 (CMIP5) GCMs. The performances of four bias co...
The objectives of this study were to: (1) evaluate possible deviations in annual and seasonal maximum (Tmx) and minimum (Tmn) temperatures, and, (2) determine the spatial pattern of these temperature changes. The study used statistical downscaling of the Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) under four r...
This study assesses the water resources and environmental challenges of Lagos mega city, Nigeria, in the context of climate change. Being a commercial hub, the Lagos population has grown rapidly causing an insurmountable water and environmental crisis. In this study, a combined field observation, sample analysis, and interviews were used to assess...
In this study, a non-local MOS is proposed for the downscaling of daily rainfall of couple model intercomparison project phase 5 (CMIP5) GCMs for the projections of rainfall in Peninsular Malaysia for two representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5. Projections of eight GCMs for both the mentioned RCPs were used for thi...
Although the complexity of physically based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensi...
Groundwater is regarded as one of the most reliable and vulnerable sources of drinking water in many countries. Declining groundwater levels, due to over-exploitation and climate-change impacts, emphasize the need for sustainable management of this valuable resource. The concept of reliability-resiliency-vulnerability (RRV) has been adopted in this...
The northern sub-Himalayan region is the primary source of water for a large part of Pakistan. Changes in precipitation and precipitation extremes in the area may have severe impacts on water security and hydrology of Pakistan. The objective of the study is to evaluate the spatial characteristics of the trends in annual and seasonal precipitation a...
The changing characteristics of aridity over a larger spatiotemporal scale have gained interest in recent years due to climate change. The long-term (1901–2016) changes in spatiotemporal patterns of annual and seasonal aridity during two major crop growing seasons of Pakistan, Kharif and Rabi, are evaluated in this study using gridded precipitation...
The uncertainties in climate projections in arid regions are quite high due to the large variability of climate and the lack of high-quality climate observations. In this study, an ensemble of four Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Model (GCM) namely GISS-E2-H, HadGEM2-ES, MIROC5, and NorESM1-M simulations wa...
The rising temperature due to global warming has caused an increase in frequency and severity of heat waves across the world. A statistical model known as Quantile Regression Forests (QRF) has been proposed in this study for the prediction of heat waves in Pakistan for different time-lags using synoptic climate variables. The gridded daily temperat...
Mean and variability of annual and seasonal rainfall in Malaysia are changing due to climate change. The estimation of the return period of extreme rainfall events based on stationary assumption may therefore not be valid in the context of climate change. Estimation of return period of extreme rainfall events for Peninsular Malaysia considering the...
We assessed the changes in meteorological drought severity and drought return periods during cropping seasons in Afghanistan for the period of 1901 to 2010. The droughts in the country were analyzed using the standardized precipitation evapotranspiration index (SPEI). Global Precipitation Climatology Center rainfall and Climate Research Unit temper...
Advance knowledge of solar radiation is highly essential for multiple energy devotions such as sustainability in energy production and development of solar energy system. The current research investigates the capability of four data mining computation models, namely random forest (RF), random tree, reduced error pruning trees and hybrid model of ra...
The presence of long‐term persistence (LTP) in hydro‐climatic time series can lead to considerable change in the significance of trend. Therefore, past findings of climatic trend analysis without considering LTP in time series has become a disputable issue. The objective of this study is to assess the spatial patterns in the trends of annual and se...
General Circulation Models (GCMs) provide vital information on the likely future climate, much needed for theeffective planning and management of water resources. The performance assessment of GCMs has receivedsignificant attention in recent years for reliable estimation of future climate. Even though many approaches havebeen trialled in the rankin...
The climate modelling community has trialled a large number metrics to evaluate the temporal performance of the Global Circulation Models (GCMs) for the selection of GCMs, while very little attention has been given to spatial performance of GCMs which is equally important. This study evaluated the performance of 20 Coupled Model 15 Intercomparison...
The rough topography, harsh climate, and sparse monitoring stations have limited hydro-climatological studies in arid regions of Pakistan. Gauge-based gridded precipitation datasets provide an opportunity to assess the climate where stations are sparsely located. Though, the reliability of these datasets heavily depends on their ability to replicat...
Changes in the temperature and precipitation have significantly affected water resources and agricultural productions in many countries across the world. The objective of the present study is to analyze the changing patterns of annual and seasonal precipitation and temperature in Iraq for the period 1961–2010. Monthly gridded precipitation and temp...
The uncertainty assessment of the changes in drought characteristics due to climate change has caught the attention of the scientific community. This study used gauge-based gridded precipitation data obtained from Global Precipitation Climatology Centre (GPCC) to reconstruct historical droughts and downscale future precipitation projected by seven...
Increased frequency and severity of heat wave is one of the immediate and certain impacts of rising temperature due to global warming. A number of heat wave related indices considering both daily maximum and minimum temperature are proposed in this paper to assess the changes in different characteristics of heat waves in Pakistan, which is one of t...
The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum...
Abstract
A hybrid approach by combining the past performance and the envelope methods has been proposed for the selection of an ensemble of general circulation models (GCMs) of Couple Model Intercomparison phase 5 (CMIP5) for the projection of spatiotemporal changes in annual and seasonal temperatures of Iraq for four representative concentration p...
Assessment of the influence of climate variables on drought characteristics is important for adaption to changing pattern of droughts due to climate change. The objective of this study is to assess the changing characteristics of droughts due to climate variability and change during two major cropping seasons (Rabi and Kharif) for the period 1901–2...
Homogeneity evaluations are usually performed on the total annual precipitation data, which often fails to detect non-homogeneity in seasonal precipitation. Furthermore, it is required to assess homogeneity using multiple methods as the performance of homogeneity testing methods depend on the distribution of the data. This is particularly important...
Abstract: A copula based methodology is presented in this study for bivariate flood frequency
analysis over a station over a Kelantan river basin located in Northeast Malaysia. The joint
dependence structures of three flood characteristics, namely, peak flow, flood volume and flood
duration were modelled using Gumble Copula. Various univariate dist...
Abstract: A copula based methodology is presented in this study for bivariate flood frequency
analysis over a station over a Kelantan river basin located in Northeast Malaysia. The joint
dependence structures of three flood characteristics, namely, peak flow, flood volume and flood
duration were modelled using Gumble Copula. Various univariate dist...
An index has been developed for the assessment of geographical distribution of susceptibility to hydrological hazards using easily available climate data. Catastrophe fuzzy theory and data clustering methods were used to avoid subjectivity in the estimation of the index of multiple climate indicators. The proposed index was used for the estimation...
Statistical models were developed for downscaling reanalysis data to monthly precipitation at 48 observation stations scattered across the Australian State of Victoria belonging to wet, intermediate and dry climate regimes. Downscaling models were calibrated over the period 1950–1991 and validated over the period 1992–2014 for each calendar month,...
Bivariate frequency analysis of flood variables of different station locations of Kelantan river basin was conducted using copula for the assessment of the geographical distribution of flood risk. Seven univariate distribution functions of flood variables were fitted with flood variables such as peak flow, flood volume, and flood duration to find t...
The selection of inputs (predictors) to downscaling models is an important task in any statistical downscaling exercise. The selection of an appropriate set of predictors to a downscaling model enhances its generalization skills as such set of predictors can reliably explain the catchment-scale hydroclimatic variable (predictand). Among the predict...
The presence of autocorrelation and long-term persistence (LTP) can lead to considerable change in the significance of trends in hydro-climatic time series. This therefore casts doubt on past findings of climatic trend studies that did not consider LTP. We assessed the trends in spatio temporal patterns of annual and seasonal precipitation of Pakis...
Gauge-based gridded precipitation estimates are emerged as a supplementary source of precipitation data where in-situ precipitation data are not readily available. In this study, four widely used gauge-based gridded precipitation products, namely Global Precipitation Climatology Centre (GPCC), Climatic Research Unit (CRU), Asian Precipitation Highl...
Developers are increasingly looking for the best management practices to reduce the risk of floods in rapidly growing urban areas. Low impact development (LID) is regarded as one of the most suitable solutions for urban stormwater management and thus the U.S. EPA's (Environmental Protection Agency) SWMM5.1 (Storm Water Management Model) added the h...
Downscaling rainfall in an arid region is much challenging compared to wet region due to erratic and infrequent behaviour of rainfall in the arid region. The complexity is further aggregated due to scarcity of data in such regions. A multilayer perceptron (MLP) neural network has been proposed in the present study for the downscaling of rainfall in...
Droughts are usually destructive when they coincide with crop growing season. Cross-seasonal drought characterization can better inform drought mitigation efforts. The present study relies on precipitation data from the Global Precipitation Climatology Centre to reconstruct historical droughts during different climatic seasons in Balochistan provin...
Downscaling Global Circulation Model (GCM) output is important in order to understand the present climate as well as future climate changes at local scale. In this study, Radial basis function (RBF) neural network was used to downscale the mean monthly rainfall in an arid coastal region located in Baluchistan province of Pakistan. The RBF model was...