Satellite-based rainfall estimation and discharge measurement of Middle Indus River, Pakistan

Younis, Syed Muhammad Zubair; Majid, Muhammad; Ammar, Ahmad

doi:10.1007/s12517-017-3192-9

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…These models include hydrological model like Areal Nonpoint Source Watershed Environment Response Simulation (ANSWERS) [14], Precipitation Runoff Modeling System (PRMS) [15], Agricultural Nonpoint Source model (AGNPS) [16], Water Erosion Prediction Project (WEPP) [17], CASCade of planes in 2-Dimensions (CASCAD) [18], Hydrological Simulation Program-Fortran (HSPF) [19], Soil and Water Assessment Tool (SWAT) [20], Large-Scale Catchment Model (LASCAM) [21], Dynamic Watershed Simulation Model (DWSM) [22], Agricultural Non-point Source Pollution model (AGNPS) [23]. Also, alteration in Land Use/Land Cover (LULC) have resulted in hydrological changes in a river basin, established through some models like HEC-HMS [24,25], Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) [26], Variable Infiltration Capacity (VIC) hydrological mode [27], and SWAT [28][29][30]. Of all these models, the applicability and use of the SWAT model established by USDA-ARS (United States Department of Agriculture-Agricultural Research Service) is considered practical.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Suitability of the SWAT Model for Hydro-Meteorological Analysis in the Lower Gangetic Floodplain Region of India

Pu,

Shivashankar,

Kundu

2024

Preprint

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In Tropical Monsoon climates, precipitation exceeds evapotranspiration, leading to increased surface runoff, especially in floodplain regions. The Bhagirathi-Hooghly River in India is the focus of the study, which analyses hydrology, sediment yield, and water balance in this floodplain area. This investigation employs the Soil and Water Assessment Tool (SWAT) model within the ArcGIS environment, using remote sensing data. The study area is divided into 4 sub-basins and 40 Hydrological Response Units (HRUs), with a focus on Land Use/Land Cover (LULC) parameters, soil attributes, and slope characteristics. Calibration (1998-2010) and validation (2011-2018) of river discharge and sediment yield are performed using the SUFI-2 algorithm within SWAT-CUP. The calibration process shows a strong correlation between observed and simulated data points, indicating the model's accuracy. The study reveals a pattern of early-year evapotranspiration followed by increasing rainfall during the monsoon season, leading to heightened surface runoff and sediment yield. Excessive rainfall, therefore, emerges as a pivotal driver of flood incidences within the floodplain. The insights derived from the SWAT model's floodplain data have the potential to inform flood control and sedimentation mitigation strategies. The assimilation of this data can empower local stakeholders and contribute to sustainable livelihoods and improved living conditions, offering guidance for future governmental policies.

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Section: Introductionmentioning

confidence: 99%

Assessing the Suitability of the SWAT Model for Hydro-Meteorological Analysis in the Lower Gangetic Floodplain Region of India

Pu,

Shivashankar,

Kundu

2024

Preprint

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“…Value in the context of data enabled by open data technologies for secondary stakeholders such as citizens implies that it enables improving quality of life of the citizens, better understanding of government actions that directly affect the citizens, improved decision-making in their daily-life activities, and innovation and development by analyzing data through its extraction and transformation (Máchová, Hub, & Lnenicka, 2018;Susha, Grönlund, & Janssen, 2015). For instance, citizens may use open data technologies education-related open government data for viewing schools in her surroundings and understanding government policies for developing educational policies country-wide (PDP, 2018), scientists may use open data technologies to obtain rainfall data for the purpose of making modeling, simulations, visualizations and improved methods for accurate predictions of disasters (Younis, Majid, & Ammar, 2017), developers can develop interactive web and desktop applications (Susha et al, 2015), data analysts can make better business decisions by integrating government data with business data, tourists can explore new regions for expedition, students can perform policy research and write academic publications (Zuiderwijk et al, 2015), named a few.…”

Section: Introductionmentioning

confidence: 99%

Predictors for the Adoption of Open Data Technologies

et al. 2020

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Open Data initiative is attracting considerable interest globally due to the growing phenomena of transparency, accountability, quality of life, and business. The adoption of open data technologies is inevitably an issue to better exploit the full potential and benefits of open data available to the public. The main issue in our knowledge of open data technologies is the scarcity of research studies on the adoption of open data technologies. Thus, the main objective of this study is to predict and explain the factors that influence the adoption of open data technologies. A Unified Model of Electronic Government Adoption (UMEGA) was employed as a lens to examine the influencing factors including additional factors i.e. imitating the behavior of others, disregarding own beliefs, and grievance redressal to make a novel contribution in the adoption studies. The survey method was used to collect the data from citizens and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique in SmartPLS 3. Satisfactory results are obtained proving that facilitating conditions has a significant positive influence on effort expectancy, effort expectancy on performance expectancy, performance expectancy on attitude, and attitude on behavioral intention to adopt open data technologies even though the number of participants is very small. Implications for the academics and managers are also outlined. Future researchers should find more concrete pieces of evidence upon collecting a large number of responses.

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A novel bias correction framework of TMPA 3B42 daily precipitation data using similarity matrix/homogeneous conditions

Choubin

Khalighi-Sigaroodi

Mishra

et al. 2019

Science of The Total Environment

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Satellite-based rainfall estimation and discharge measurement of Middle Indus River, Pakistan

Cited by 3 publications

References 8 publications

Assessing the Suitability of the SWAT Model for Hydro-Meteorological Analysis in the Lower Gangetic Floodplain Region of India

Assessing the Suitability of the SWAT Model for Hydro-Meteorological Analysis in the Lower Gangetic Floodplain Region of India

Predictors for the Adoption of Open Data Technologies

A novel bias correction framework of TMPA 3B42 daily precipitation data using similarity matrix/homogeneous conditions

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