ORCID Profile
0000-0001-9442-5664
Current Organisation
Universität Rostock
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Publisher: MDPI AG
Date: 30-09-2021
DOI: 10.3390/RS13193916
Abstract: Rapid and reliable flood information is crucial for minimizing post-event catastrophes in the complex river basins of the world. The Chenab River basin is one of the complex river basins of the world, facing adverse hydrometeorological conditions with unpredictable hydrologic response. Resultantly, many vicinities along the river undergo destructive inundation, resulting in huge life and economic losses. In this study, Hydrologic Engineering Centre–Hydrologic Modeling System (HEC-HMS) and HEC–River Analysis System (HEC-RAS) models were used for flood forecasting and inundation modeling of the Chenab River basin. The HEC-HMS model was used for peak flow simulation of 2014 flood event using Global Precipitation Mission (GMP) Integrated Multisatellite Retrievals-Final (IMERG-F), Tropical Rainfall Measuring Mission_Real Time (TRMM_3B42RT), and Global Satellite Mapping of Precipitation_Near Real Time (GSMaP_NRT) precipitation products. The calibration and validation of the HEC-RAS model were carried out for flood events of 1992 and 2014, respectively. The comparison of observed and simulated flow at the outlet indicated that IMERG-F has good peak flow simulation results. The simulated inundation extent revealed an overall accuracy of more than 90% when compared with satellite imagery. The HEC-RAS model performed well at Manning’s n of 0.06 for the river and the floodplain. From the results, it can be concluded that remote sensing integrated with HEC-HMS and HEC-RAS models could be one of the workable solutions for flood forecasting, inundation modeling, and early warning. The concept of integrated flood management (IFM) has also been translated into practical implementation for joint Indo-Pak management for flood mitigation in the transboundary Chenab River basin.
Publisher: MDPI AG
Date: 11-05-2020
DOI: 10.3390/SU12093905
Abstract: Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 °C for Tmax and 3.2 °C for Tmin under A2 as well as 2.7 °C for Tmax and 3.2 °C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 °C under the A2 scenario and 7.7 and 6.8 °C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm−3 and 0.7 to 0.56 kgm−3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.
Publisher: MDPI AG
Date: 27-08-2020
DOI: 10.3390/RS12172782
Abstract: The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.
No related grants have been discovered for Muhammad Waseem.