DOCSLIB.ORG

A Regional Blended Precipitation Dataset Over Pakistan Based On

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Regional Blended Precipitation Dataset Over Pakistan Based On remote sensing Article A Regional Blended Precipitation Dataset over Pakistan Based on Regional Selection of Blending Satellite Precipitation Datasets and the Dynamic Weighted Average Least Squares Algorithm Khalil Ur Rahman and Songhao Shang * State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; [email protected] * Correspondence: [email protected]; Tel.: +86-10-6279-6674 Received: 25 October 2020; Accepted: 4 December 2020; Published: 8 December 2020 Abstract: Substantial uncertainties are associated with satellite precipitation datasets (SPDs), which are further amplified over complex terrain and diverse climate regions. The current study develops a regional blended precipitation dataset (RBPD) over Pakistan from selected SPDs in different regions using a dynamic weighted average least squares (WALS) algorithm from 2007 to 2018 with 0.25◦ spatial resolution and one-day temporal resolution. Several SPDs, including Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG), Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42-v7, Precipitation Estimates from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), ERA-Interim (reanalysis dataset), SM2RAIN-CCI, and SM2RAIN-ASCAT are evaluated to select appropriate blending SPDs in different climate regions. Six statistical indices, including mean bias (MB), mean absolute error (MAE), unbiased root mean square error (ubRMSE), correlation coefficient (R), Kling–Gupta efficiency (KGE), and Theil’s U coefficient, are used to assess the WALS-RBPD performance over 102 rain gauges (RGs) in Pakistan. The results showed that WALS-RBPD had assigned higher weights to IMERG in the glacial, humid, and arid regions, while SM2RAIN-ASCAT had higher weights across the hyper-arid region. The average weights of IMERG (SM2RAIN-ASCAT) are 29.03% (23.90%), 30.12% (24.19%), 31.30% (27.84%), and 27.65% (32.02%) across glacial, humid, arid, and hyper-arid regions, respectively. IMERG dominated monsoon and pre-monsoon seasons with average weights of 34.87% and 31.70%, while SM2RAIN-ASCAT depicted high performance during post-monsoon and winter seasons with average weights of 37.03% and 38.69%, respectively. Spatial scale evaluation of WALS-RPBD resulted in relatively poorer performance at high altitudes (glacial and humid regions), whereas better performance in plain areas (arid and hyper-arid regions). Moreover, temporal scale performance assessment depicted poorer performance during intense precipitation seasons (monsoon and pre-monsoon) as compared with post-monsoon and winter seasons. Skill scores are used to quantify the improvements of WALS-RBPD against previously developed blended precipitation datasets (BPDs) based on WALS (WALS-BPD), dynamic clustered Bayesian model averaging (DCBA-BPD), and dynamic Bayesian model averaging (DBMA-BPD). On the one hand, skill scores show relatively low improvements of WALS-RBPD against WALS-BPD, where maximum improvements are observed in glacial (humid) regions with skill scores of 29.89% (28.69%) in MAE, 27.25% (23.89%) in ubRMSE, and 24.37% (28.95%) in MB. On the other hand, the highest improvements are observed against DBMA-BPD with average improvements across glacial (humid) regions of 39.74% (36.93%), 38.27% (33.06%), and 39.16% (30.47%) in MB, MAE, and ubRMSE, respectively. It is recommended that the development of RBPDs can be a potential alternative for data-scarce regions and areas with complex topography. Remote Sens. 2020, 12, 4009; doi:10.3390/rs12244009 www.mdpi.com/journal/remotesensing Remote Sens. 2020, 12, 4009 2 of 31 Keywords: blended precipitation datasets; weighted average least squares algorithm; regional and seasonal evaluation; complex topography; diverse climate; Pakistan 1. Introduction Precipitation estimates with high precision is essential to amend the regional and global scale hydrological and climate processes, and their impact [1,2]. Precipitation, ranked first by the Global Climate Observing System (GCOS), is extremely difficult to measure with high precision over the complex mountainous terrain and diverse climate across Pakistan and other similar regions [1–5]. Moreover, the temporal and spatial variations of precipitation add to the complexities in its precise estimation [6,7], particularly in poorly or ungauged catchments. Satellite precipitation datasets (SPDs) provide estimates of precipitation at a large scale as compared with rain gauges (RGs) and radars [8]. The performance of SPDs is significantly dependent on the retrieval algorithms and climatic regions [9,10]. Advancements in retrieval algorithms of SPDs and reanalysis precipitation products have been continuous [11–13]; however, there are still considerable sources and magnitude of errors [14–16]. Therefore, the assimilation of precipitation estimates from multiple sources SPDs into a blended dataset considering the weaknesses and strengths of an individual blending SPD is strongly recommended [2]. Considering a blended dataset, several efforts have been made in this regard, where the first blending was reported in the mid-1980s by merging radar-gauge precipitation [17]. The Global Precipitation Climatology Project (GPCP), an earlier attempt to blend satellite-gauge data, is a monthly temporal and 0.25◦ spatial resolutions dataset developed using a mean bias-corrected method and an inverse-error-variance weighting method [18]. Similarly, the Climate Prediction Center Merged Analysis of Precipitation (CMAP) having monthly temporal and 2.5◦ spatial resolutions with 17 years of availability period is developed by merging RGs, SPDs, and reanalysis datasets employing the maximum likelihood estimation method [19]. Since then, a number of approaches, such as improvements in calibration algorithms, adopting the relative weights techniques, reduction in sampling issues, application of dynamic methods to estimate SPDs weights, etc., have been employed to develop blended precipitation datasets (BPDs) having high-quality estimates [1–5,20–25]. Several studies have reported significantly improved performances of the BPDs in quantification and evaluation of precipitation estimates and also in hydrological and meteorological applications [26,27]. Several BPDs have been developed across different regions of the globe [2,5,23,28,29]. The methods used to develop BPDs include Bayesian model averaging [3,5,30], conditional merging [31,32], simple scaling method [32], data assimilation [12], variation approach [20], probability density function [21], simple model averaging [29], principal component analysis [24], neural network analysis [33], and the non-parametric kernel merging method [34]. A detailed description of techniques to blend SPDs is available in references [22,34–36]. Very limited studies have focused on the development and evaluation of BPDs across the complex topography and diverse climate of Pakistan. Muhammad et al. [37] developed a regional precipitation algorithm that incorporated the inconsistency issues and error of individual SPDs. The developed algorithm was based on regional performance weights augmented by the leave-one-out cross validation (LOOCV) and ensemble algorithm. They reported significant improvements in the developed regional precipitation algorithm as compared with individual SPDs. Rahman et al. [24] developed a BPD employing the sample t-test comparison and principal component analysis (PCA) to blend SPDs, i.e., Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG) and Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B43-v7. The analyses depicted that the PCA-BPD outperformed all the SPDs and proved to be superior to the regional precipitation algorithm developed by Waseem et al. [37]. Similarly, Rahman et al. [1,3] developed BPDs using the dynamic Bayesian model averaging (DBMA) and Remote Sens. 2020, 12, 4009 3 of 31 dynamic clustered Bayesian averaging (DCBA), by utilizing precipitation estimates from TMPA 3B42-v7, Precipitation Estimates from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), ERA-Interim (reanalysis dataset), and Climate Prediction Center morphing technique (CMORPH) at a daily temporal scale for 16 years (2000–2015). Very recently, Rahman et al. [4] developed BPD using the weighted average least squares (WALS) method using the same combination of SPDs from 2000 to 2015. Overall, the results presented a comprehensively improved performance of WALS-BPD and DCBA-BPD as compared with DBMA-BPD. However, there is a specific pattern of error distribution across Pakistan, both spatially (high error in glacial and humid regions) and temporally (high error in monsoon season). The error shows a decreasing trend from DBMA-BPD to DCBA-BPD and WALS-BPD, but there is still a considerable magnitude of errors, which must be addressed. The above BPDs used the same set of SPDs in all climate regions. However, it is evident that different SPDs perform differently in diverse climate regions. The present study is an attempt to address the high magnitude of errors across glacial and humid regions by considering the spatial and temporal variations of SPDs, and develops a dynamic regional BPD (hereinafter, WALS-RBPD) by selecting appropriate blending SPDs for different climate regions and employing a robust and sophisticated
Load more

Recommended publications
  • The Sustainable Development of the China Pakistan Economic Corridor: Synergy Among Economic, Social, and Environmental Sustainability
    sustainability Article The Sustainable Development of the China Pakistan Economic Corridor: Synergy among Economic, Social, and Environmental Sustainability Muhammad Awais 1 , Tanzila Samin 2 , Muhammad Awais Gulzar 3,* and Jinsoo Hwang 4,* 1 Department of Data Science & Engineering Management, School of Management, Zhejiang University, Hangzhou 310058, China; [email protected] 2 School of Business Management, NFC Institute of Engineering & Fertilizer Research, Faisalabad 38000, Pakistan; [email protected] 3 Waikato Management School, The University of Waikato, Hamilton 3240, New Zealand 4 Department of Food Service Management, Sejong University, Seoul 143-747, Korea * Correspondence: [email protected] (M.A.G.); [email protected] (J.H.); Tel.: +8615558031661 (M.A.G.); +82-2-3408-4072 (J.H.) Received: 11 October 2019; Accepted: 3 December 2019; Published: 9 December 2019 Abstract: This case study focuses on how economic, social and environmental factors synergize for sustainable development, and relates to fundamental speculations, looking to unclutter a query-encompassing view of the China Pakistan Economic Corridor (CPEC). This study is explanatory in nature, and identifies, recognizes, and discusses the social dispositions and fundamental sustainability dimensions related to sustainable development. Three fundamental sustainability dimensions—economic, social and environmental—are incorporated in connection with the CPEC to explore sustainable development. We submit an inclusive viewpoint of the CPEC, towards the
    [Show full text]
  • PAKISTAN STUDIES Topical Solved Geography 2007 – 2019
    0448/02 and 2059/02 | Geography Environment of Pakistan PAKISTAN STUDIES Topical Solved Geography 2007 – 2019 In this booklet, Questions in the Past Papers of whole June Series for IGCSE 0448/02 and O Level 2059/02 Environment of Pakistan (Geography) are same. Questions of November series are taken from O Level Past Papers, but they are also beneficial for IGCSE students for more practice and better preparation to enhance their grades in CAIEs exams. Solved By: SHAKIL ANWAR Beaconhouse School System, M.Sc. (Geography / University Distinction) Garden Town Campus, Lahore (History) Academia: Center of Excellence, M.A. P Block, Model Town Ext. Lahore M.A. (Political Science) Phone: 0332-4858610 M.A. (Teacher Education) Email: [email protected] Solved by: Shakil Anwar (03324858610) CONTENTS Unit: Introduction 0.1 About the Author 0.2 Table of Contents 0.3 The Land of Pakistan Unit 1: The Natural Topography, including drainage 1.1 Northern, North-Western and Western Mountains 1.2 The Desert Areas Unit 2: Climate 2.1 Climatic Elements (Temperature, Rainfall, Winds etc 2.2 Effects of Climate on Life of the People 2.3 Climatic Hazards (Floods, Storms, Soil Erosion, Draughts etc.) Unit 3: Natural Resources-an Issue of Sustainability of Water 3.1 Rivers and Dams of Pakistan 3.2 Irrigation System 3.3 Indus Water Treaty 3.4 Water-logging and Salinity 3.5 Water Deficiency/Water Pollution Unit 4: Forests 4.1 Types of Forests in Pakistan 4.2 Importance/Uses of Forests 4.3 Afforestation/Deforestation and Solutions Unit 5: Mineral Resources
    [Show full text]
  • Topography of Pakistan”
    whatsapp: +92 323 509 4443, email: [email protected] Chapter 1 “Topography of Pakistan” www.megalecture.com www.youtube.com/megalecture Page 1 of 26 whatsapp: +92 323 509 4443, email: [email protected] Definitions: Topography : it is the detailed study of the surface features of a region. ● Hills and Mountains: A Hill is generally considered to be an elevated piece of land less than 600 - 610 meters high, and a Mountain is an elevation of land that is more than 610m high. Some hills are called mountains while some mountains are referred to as hills. ● A Mountain Range is a succession of mountains which have the same direction, age and same causes of formation etc A snowfield is a huge permanent expanse of snow ● Relief/ topography: the condition of the land related to the rocks,ups and dowrs eroded and depositional features like valleys, rock type,passes etc ● Drainage :it is related to the eroded and depoditional! Features of the rivers like ox-low lake,meander,levees etc .all tyeps of river patterns including dendafric is part of drainage. ● Gorges :they are an irregular depression in a valley. ● Cirque : are regular depression made by the movment of glaciers. ● Valley: plain land between two mountains. ● Passes: a natural path which connects two areas in mountainous region. ● Snowfield : A plain field covered with snow usually above the snow line (4000m) ● Ravine :A deep narrow gorge with steep sides ● Gully : A revine formed by water activity ● Glaciers:Tongue shaped mass of ice moving slow down the valley ● Streams /Springs:
    [Show full text]
  • Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan
    Article Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan Asid Ur Rehman 1,2, Farrukh Chishtie 3,*, Waqas A. Qazi 1, Sajid Ghuffar 1, Imran Shahid 1 and Khunsa Fatima 4 1 Department of Space Science, Institute of Space Technology (IST), Islamabad 44000, Pakistan; [email protected] (A.U.R.); [email protected] (W.A.Q.); [email protected] (S.G.); [email protected] (I.S.) 2 Hagler Bailly Pakistan, Islamabad 44000, Pakistan 3 SERVIR-Mekong, Asian Disaster Preparedness Center (ADPC), Bangkok 10400, Thailand 4 Institute of Geographical Information System (IGIS), National University of Science and Technology (NUST), Islamabad 44000, Pakistan; [email protected] * Correspondence: [email protected]; Tel.: +66-0909-29-1450 Received: date:14 October 2018; Accepted: 11 December 2018; Published: 14 December 2018 Abstract: Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE).
    [Show full text]
  • DAWOOD PUBLIC SCHOOL the ENVIRONMENT of PAKISTAN SYLLABUS for the YEAR 2010-2011 CLASS: IX Paper 2 (2059/02)
    1 DAWOOD PUBLIC SCHOOL THE ENVIRONMENT OF PAKISTAN SYLLABUS FOR THE YEAR 2010-2011 CLASS: IX Paper 2 (2059/02) SUMMARY OF SYLLABUS The ‘Aims and Objectives’ is to include interpretation, analysis and evaluation of resources. Whilst knowledge and understanding are important, the syllabus also aims to develop skills in using resources such as maps and graphs. It also aims to stimulate discussion on the issues and challenges raised. It also helps to develop resource skills and should encourage the students to express opinions and make evaluations. LIST OF CONTENT 1. THE LAND OF PAKISTAN • Latitudes and longitudes ( Introduction of Pakistan) • List of rivers and their location ( Topography) • Distribution of temperature and rainfall (Climate) 2. NATURAL RESOURCES • Water resources its shortages and pollution • Forests as a resource • Minerals resources. Limestone, Gypsum and Rock salt • Problems of development of mineral resources • Development of the fishing industry • Sustainability of these resources. 3. AGRICULTURAL DEVELOPMENT • Agriculture as a system • Crops • Livestock Farming • Fruits and Vegetables • The advantages and disadvantages of agricultural development • The issue of the sustainability of agricultural development AIMS AND OBJECTIVES The syllabus aims to give student a knowledge and understanding of the importance to the people and country of Pakistan of its physical characteristics, human and natural resources, economic development, population characteristics, and of their inter-relationships. The students will be assessed for their attainment in each of the objectives, in the following weighting Approx. Weighting • Ability to show knowledge and understanding of physical and human environments 55% • Ability to evaluate information by identifying advantages and disadvantages of developments 20% • Ability to interpret and analyze a variety of resources 25% SCHEME OF ASSESSMENT • The annual and mid-term examination consists of one written paper of 11/2 hours’ duration • Five questions will be set, each made up of a series of sub-parts.
    [Show full text]
  • O Level Pakistan Studies 2059/02 Paper 2 the Environment of Pakistan
    Cambridge International Examinations Cambridge Ordinary Level *5936860792* PAKISTAN STUDIES 2059/02 Paper 2 The Environment of Pakistan May/June 2018 1 hour 30 minutes Candidates answer on the Question Paper. Additional Materials: Ruler READ THESE INSTRUCTIONS FIRST Write your name, Centre number and candidate number in the spaces provided. Write in dark blue or black pen. Do not use staples, paper clips, glue or correction fluid. DO NOT WRITE IN ANY BARCODES. Answer any three questions. The Insert contains Figs. 1.2 and 1.3 for Question 1 and Figs. 3.1 and 3.2 for Question 3. The Insert is not required by the Examiner. The number of marks is given in brackets [ ] at the end of each question or part question. This document consists of 23 printed pages, 1 blank page and 1 Insert. DC (RW/SG) 152770/8 © UCLES 2018 [Turn over 2 1 (a) Study Fig. 1.1, a map of Pakistan. Key: international boundary province-level boundary JAMMU & disputed boundary KASHMIR disputed territory N 0 100 200 300 Arabian Sea km Fig. 1.1 (i) On Fig. 1.1, label the following: Afghanistan; India; Line of longitude 70°E You should write the name in the correct location on the map. [3] (ii) On Fig. 1.1, draw and label the Tropic of Cancer. [2] (iii) Describe Pakistan’s location in relation to other countries in South and Central Asia. ........................................................................................................................................... ..........................................................................................................................................
    [Show full text]
  • Contribution of Changing Precipitation and Climatic Oscillations In
    www.nature.com/scientificreports OPEN Contribution of changing precipitation and climatic oscillations in explaining variability of water extents of large reservoirs in Pakistan Ibrar ul Hassan Akhtar 1,3 & H. Athar 1,2* Major threat that Pakistan faces today is water scarcity and any signifcant change in water availability from storage reservoirs coupled with below normal precipitation threatens food security of more than 207 million people. Two major reservoirs of Tarbela and Mangla on Indus and Jhelum rivers are studied. Landsat satellite’s data are used to estimate the water extents of these reservoirs during 1981–2017. A long-term signifcant decrease of 15–25% decade−1 in water extent is found for Tarbela as compared to 37–70% decade−1 for Mangla, mainly during March to June. Signifcant water extents reductions are observed in the range of −23.9 to −53.4 km2 (1991–2017) and −63.1 to −52.3 km2 (2001–2010 and 2011–2017) for Tarbela and Mangla, respectively. The precipitation amount and areas receiving this precipitation show a signifcant decreasing trend of −4.68 to −8.40 mm year−1 and −358.1 to −309.9 km2 year−1 for basins of Mangla and Tarbela, respectively. The precipitation and climatic oscillations are playing roles in variability of water extents. The ensuing multiple linear regression models predict water extents with an average error of 13% and 16% for Tarbela and Mangla, respectively. The Asian Waters and River Basins Fresh water resources being scarce can’t be taken as granted and there is a need to identify the hotspots for adap- tation in major river basins of Asia1.
    [Show full text]
  • Map 6 Asia Orientalis Compiled by M.U
    Map 6 Asia Orientalis Compiled by M.U. Erdosy, 1997 Introduction Map 6 embraces four distinct regions: central Asia and the Indus valley, which had lengthy contacts with the Greeks and Romans; and Tibet and Chinese Turkestan, which had practically none. The first two entered Western consciousness through the eastward expansion of the Achaemenid empire, which brought them into the orbit of Greek geographical knowledge, and won them prominence as the theaters of Alexander the Great’s eastern campaigns. Although colonization in the wake of Macedonian conquests was short-lived, classical influence on the arts and crafts of the area, if not its religious and political institutions, remained prominent for centuries. Moreover, even though the Parthians and Sasanians effectively severed overland links between central Asia and the Mediterranean world, the Alexander legend helped preserve geographical information for posterity (albeit frequently in a distorted form), even if little in the way of fresh data was added until Late Roman times. By contrast, areas to the north and east of the Himalayas remained in effect terra incognita until the nineteenth century, when the heart of Asia first received serious exploration by westerners, mostly as a by-product of the “Great Game.” Despite the impressive lists of toponyms and ethnonyms found in Ptolemy’s Geography and Ammianus Marcellinus, few cities and tribes can be localized with any certitude, since ancient geographers not only lacked first-hand knowledge of the area, but were also hampered by a defective image of the world, which was sure to produce serious distortions in peripheral regions. As a result, the eastern half of Map 6 is largely devoid of identifiable sites (although it contributes extensively to the list of unlocated toponyms and ethnonyms), while the western half is densely populated.
    [Show full text]
  • Geotechnical Aspects of Recent Extreme Floods in Pakistan; a Case History
    Missouri University of Science and Technology Scholars' Mine International Conference on Case Histories in (2013) - Seventh International Conference on Geotechnical Engineering Case Histories in Geotechnical Engineering 03 May 2013, 10:55 am - 11:10 am Geotechnical Aspects of Recent Extreme Floods in Pakistan; A Case History Sarfraz Ali University of Witwatersrand, South Africa Fawad Akram National University of Sciences & Technology, Pakistan Abdul Qudoos Khan University of Witwatersrand, South Africa Misba-Hafsa National University of Sciences & Technology, Pakistan Follow this and additional works at: https://scholarsmine.mst.edu/icchge Part of the Geotechnical Engineering Commons Recommended Citation Ali, Sarfraz; Akram, Fawad; Khan, Abdul Qudoos; and Misba-Hafsa, "Geotechnical Aspects of Recent Extreme Floods in Pakistan; A Case History" (2013). International Conference on Case Histories in Geotechnical Engineering. 1. https://scholarsmine.mst.edu/icchge/7icchge/session17/1 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. This Article - Conference proceedings is brought to you for free and open access by Scholars' Mine. It has been accepted for inclusion in International Conference on Case Histories in Geotechnical Engineering by an authorized administrator of Scholars' Mine. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected].
    [Show full text]
  • Views Or Experience About the Soil Fertility Effect
    International Journal of Agriculture and Environmental Research ISSN: 2455-6939 Volume:03, Issue:02 "March-April 2017" FARMERS PERCEPTION ABOUT FLOODS EFFECTS ON AGRICULTURE LANDS ALONG THE RIVER JHELUM Raees Mehmood M. Phil Scholar Govt. College University Faisalabad, Pakistan ABSTRACT In the study farmers perception about floods effect on agriculture lands along the river Jhelum find out. The study based on primary data collection method. The study which had taken along the river Jhelum where agriculture lands exist in local language called “Bella”. In this study three hundred farmers from fifteen union councils selected through stratified random sampling technique. From each union council twenty respondents were taken. Their perceptions were found by the questionnaires. The questionnaires were in close ended form. After the collection of data SPSS software was used to analyze the data and descriptive statistical analysis performed. The results indicated by the tables and graphs. Keywords: Flood, Perception, Agriculture land, Along the River 1. INTRODUCTION Flood is natural phenomenons which do not exist only in the Pakistan but it spread on world level. Flood is a hazard when it brought destruction than called disaster. In Pakistan the province Punjab gifted by five rivers which flow on its surface in different dimension. These rivers have also benefits as well as provide loss in the form of floods. In district Jhelum the river Jhelum also present which effect on the two tehsils property and agriculture lands which lying along the river Jhelum. Husain (2015) described that in Pakistan the unfavorable climatic condition effected property and infrastructure, brought destruction in agricultural yield, rehabilitation and rebuilding costs of those areas distressed by environmental disasters.
    [Show full text]
  • Geography Today Pupil Book 1 Revised Edition
    Dawood Public School Course Outline 2019-20 Cambridge O Level Pakistan Studies Grade X Paper 2 (2059/02) Month Contents August Development of Water Resources September Power Resources October Secondary and Tertiary Industries Trade November Transport and Communication December Mid-Year Examination January Population February Revision for Mock Examination March Mock Examination Syllabus aims: The syllabus aims to give candidates a knowledge and understanding of the importance to the people and country of Pakistan of its physical characteristics, human and natural resources, economic development, population characteristics, and of their inter-relationships. The ‘Aims and Objectives’ is to include interpretation, analysis and evaluation of resources. Whilst knowledge and understanding are important, the syllabus also aims to develop skills in using resources such as maps and graphs. It also aims to stimulate discussion on the issues and a challenge raised and helps to develop resource skills and encourage the students to express opinions and make evaluations. List of Content 1. THE LAND OF PAKISTAN a) Location of Pakistan: Students should be able to identify the following on a map: Tropic of Cancer, latitudes 30°N, 36°N, longitudes 64°E, 70°E and 76°E. Arabian Sea Countries sharing a border with Pakistan, and Pakistan’s position in relation to others in South and Central Asia. b) Location of provinces and cities: Students should be able to identify the following on a map: Provinces, Northern Areas (Gilgit-Baltistan) and FATA. Cities: Islamabad, Murree, Rawalpindi, Gujranwala, Lahore, Faisalabad, Multan, Sialkot, Peshawar, Chitral, Gilgit, Hyderabad, Karachi, Quetta and Gwadar. c) The natural topography, including drainage: Students should be able to identify the following on a map: Landforms: Balochistan Plateau, Sulaiman Range, Safed Koh, Potwar Plateau, Salt Range, Hindu Kush, Karakoram and Himalaya Mountain Ranges.
    [Show full text]
  • The Environment of Pakistan, Pakistan Studies (Peak Publishing, London 2003)
    Dawood Public School Course Outline for 2013-2014 Subject Geography Class X Paper 2 (2059/02) SUMMARY OF SYLLABUS The ‘Aims and Objectives’ is to include interpretation, analysis and evaluation of resources. Whilst knowledge and understanding are important, the syllabus also aims to develop skills in using resources such as maps and graphs. It also aims to stimulate discussion on the issues and challenges raised. It also helps to develop resource skills and encourage the students to express opinions and make evaluations. LIST OF CONTENT 1. THE LAND OF PAKISTAN Latitudes and longitudes. List of rivers and their location. Distribution of temperature and rainfall. 2. NATURAL RESOURCES Water resources its shortages and pollution. Forests as a resource. Minerals resources. Limestone, Gypsum and Rock salt. Problems of development of mineral resources. Development of the fishing industry. Sustainability of these resources. 3. POWER RESOURCES Renewable and non-renewable resources. Types of non-renewable resources. The importance of renewable energy sources. 4. AGRICULTURAL DEVELOPMENT Agriculture as a system. Crops. Livestock Farming. Fruits and Vegetables. The advantages and disadvantages of agricultural development. The issue of the sustainability of agricultural development. 5. INDUSTRIAL DEVELOPMENT Industries have both secondary and tertiary. The formal and informal employment. The issue of the sustainability of industry in Pakistan. 6. TRADE Types of trade. Exports of Pakistan. Imports of Pakistan. Direction of trade. Pakistan’s trading partners. 1 7. TRANSPORT AND TELECOMMUNICATIONS Transport system of Pakistan. Modes of transportation. Global communications available to industries, business and education. 8. POPULATION Population pattern. Population composition. The present changing population structure to assess the sustainability of development.
    [Show full text]