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iForest - Biogeosciences and Forestry

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Quantitative assessment of past and future tropical forest transition and its dynamic to streamflow of the catchment, Malaysia

Mahboubeh Ebrahimian (1)   , Ahmad Ainuddin Nurruddin (2)

iForest - Biogeosciences and Forestry, Volume 17, Issue 3, Pages 181-191 (2024)
doi: https://doi.org/10.3832/ifor4339-017
Published: Jun 30, 2024 - Copyright © 2024 SISEF

Research Articles


The consequences of human interventions on land use have been empirically demonstrated to affect substantially hydrological processes and ecosystem services within watershed environments. Since 1970, Malaysia has faced deforestation, driven mainly by logging and agricultural expansion, aligning with its developmental goals by 2020. From 1970 to 2000, deforestation led to a 25.5% decline in forested land, causing a significant 10.2% rise in excess runoff. Moreover from 2001 to 2021, the nation lost 17% of its total land to deforestation. These trends emphasize the need for a thorough investigation of sustainable conservation efforts in Malaysia. This study focuses on the Langat basin in Malaysia, evaluating past and future land use changes and their effects on the basin’s hydrological response. The study employed key informant reports, population growth data, observed land use change, field survey and agricultural land availability considered for developing change scenarios. We emphasized the significance of integrating diverse modeling methods to analyze LULC changes effectively. The use of a semi-distributed hydrological model, SWAT, in combination with Markov chain and Multi-Layer Perceptron (MLP) model and Geographic Information Systems (GIS) techniques proved to be an integrated and suitable tool for comprehensive change analysis and modeling of land use. Markov chain modeling is valuable for predicting land use changes over time, providing input scenarios for SWAT simulations. MLP is a powerful algorithm to capture non-linear relationships and complex patterns in the data, enhancing the modeling accuracy. The simulation results, based on historic land use data (1984-2006-2010) and projected future land use maps (2030-2050-2080), revealed a consistent pattern of urban expansion and deforestation leading to increased streamflow. Projections indicated a substantial rise in streamflow by 20%, 61%, and 71% for the 2030s, 2050s, and 2080s, respectively. To mitigate potential flood and sediment loss, it is crucial to involve local stakeholders such as local communities, government bodies, environmental organizations, and businesses. Such analysis facilitates understanding their perspectives and concerns regarding afforestation and urban expansion control, informing future development programs and land use planning effectively.

  Keywords


Land Use Conversion, Hydrological Processes, Land Use Scenarios, Markov Chain, SWAT

Authors’ address

(1)
Mahboubeh Ebrahimian 0000-0002-0215-5634
Department of Water Resources Management, Research Institute of Hamoon International Wetland, Zabol Research Institute, Zabol (Iran)
(2)
Ahmad Ainuddin Nurruddin
Faculty of Forestry, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor (Malaysia)

Corresponding author

 
Mahboubeh Ebrahimian
mebrahimian@uoz.ac.ir

Citation

Ebrahimian M, Nurruddin AA (2024). Quantitative assessment of past and future tropical forest transition and its dynamic to streamflow of the catchment, Malaysia. iForest 17: 181-191. - doi: 10.3832/ifor4339-017

Academic Editor

Luigi Saulino

Paper history

Received: Mar 01, 2023
Accepted: Jun 26, 2024

First online: Jun 30, 2024
Publication Date: Jun 30, 2024
Publication Time: 0.13 months

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(1)
Abbaspour KC, Vejdani M, Haghighat S, Yang J (2007)
SWAT-CUP calibration and uncertainty programs for SWAT. In: Proceedings of the “MODSIM 2007 International Congress on Modelling and Simulation”. Modelling and Simulation Society of Australia and New Zealand, Canberra, Australia, pp. 1596-1602.
Gscholar
(2)
Abdul Kader SZ, Mustafa M, Sufian A (2012)
Climate change adaptation and mitigation through land use decision making in Malaysia. In: Proceedings of the “International Conference on Public Policy and Social Sciences”. UITM Melaka (Malaysia) 12 Nov 2012, pp. 11.
Online | Gscholar
(3)
Abdullah R (2003)
Short-term and long-term projection on Malaysian palm oil production. Oil Palm Industry Economic Journal 3 (1): 32-36.
Gscholar
(4)
ADB (2009)
Economics of climate change in Southeast Asia: a regional review. Economics and Research Department, Asian Development Bank - ADB, Manila, Philippines.
Online | Gscholar
(5)
Adnan NA (2010)
Quantifying the impacts of climate and land use changes on the hydrological response of a monsoonal catchment. PhD thesis, Faculty of Social and Human Sciences, University of Southampton, UK, pp. 273.
Gscholar
(6)
Agarwal C, Green GM, Grove JM, Evans TP, Schweik CM (2002)
A review and assessment of land-use change models: dynamics of space, time, and human choice. GTR NE-297, USDA Forest Service, Northeastern Research Station, Radnor, PA, USA, pp. 61.
Online | Gscholar
(7)
Ajorlo M, Abdullah RB, Yusoff MK, Halim RA, Hanif AHM, Willms WD (2013)
Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems. Environmental Monitoring and Assessment 185 (10): 8649-8658.
CrossRef | Gscholar
(8)
Arnold JG, Srinivasan S, Muttaih RS, Williams JR (1998)
Large area hydrologic modeling and assessment. Part 1: Model development. JAWRA Journal of the American Water Resources Association 34 (1): 73-89.
CrossRef | Gscholar
(9)
Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL (2011)
Soil and water assessment tool - input/output file documentation version 2009. Technical Report no. 365, Water Resources Institute, Texas A&M University, College Station, TX, USA, pp. 662.
Online | Gscholar
(10)
Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Santhi C, Harmel RD, Van Griensven A, Van Liew MW, Kannan N, Jha MK (2012)
SWAT: model use, calibration, and validation. Transactions of the ASABE 55 (4): 1491-1508.
CrossRef | Gscholar
(11)
Ayub KR, Hin LS, Abd Aziz H (2009)
SWAT application for hydrologic and water quality modeling for suspended sediments: a case study of Sungai Langat’s catchment in Selangor. In: International conference on water resources, pp. 26-27.
Gscholar
(12)
Baysal G (2013)
Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey. Master thesis, Westfälische Wilhelms-Universität, Münster, Germany, pp. 75.
Gscholar
(13)
Bruijnzeel LA (2004)
Hydrological functions of tropical forests: not seeing the soil for the trees? Agriculture, Ecosystems & Environment 104 (1): 185-228.
CrossRef | Gscholar
(14)
El-Khoury A, Seidou O, Lapen DR, Que Z, Mohammadian M, Sunohara M, Bahram D (2015)
Combined impacts of future climate and land use changes on discharge, nitrogen and phosphorus loads for a Canadian river basin. Journal of Environmental Management 151: 76-86.
CrossRef | Gscholar
(15)
Goh KJ (2000)
Agronomic requirements and management of oil palm for high yields in Malaysia. In: Proceeding of the seminar on managing oil palm for high yields: agronomic principles. Malaysia Society of Soil Science and Param Agriculture Soil Surveys, pp. 39-73.
Gscholar
(16)
He K, Zhang X, Ren S, Sun J (2016)
Deep residual learning for image recognition. In: Proceedings of the “IEEE Conference on Computer Vision and Pattern Recognition.
Gscholar
(17)
Islam M, Ahmed R (2011)
Land use change prediction in Dhaka city using GIS aided Markov chain modeling. Journal of Life and Earth Science 6: 81-89.
CrossRef | Gscholar
(18)
Juahir H, Zain SM, Yusoff MK, Hanidza TIT, Armi SM, Toriman ME, Mokhtar M (2011)
Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques. Environmental Monitoring and Assessment 173 (1-4): 625-641.
CrossRef | Gscholar
(19)
Juneng L, Tangang FT, Kang H, Lee WJ, Seng YK (2010)
Statistical downscaling forecasts for winter monsoon precipitation in Malaysia using multimodel output variables. Journal of Climate 23: 17-27.
CrossRef | Gscholar
(20)
Kafy AA, Rahman MS, Hasan MM, Islam M (2020)
Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh. Remote Sensing Applications: Society and Environment 18: 100314.
CrossRef | Gscholar
(21)
Kafy AA, Al Rakib A, Fattah MA, Rahaman ZA, Sattar GS (2022)
Impact of vegetation cover loss on surface temperature and carbon emission in a fastest-growing city, Cumilla, Bangladesh. Building and Environment 208 (14): 108573.
CrossRef | Gscholar
(22)
Kafy AA, Saha M, Fattah MA, Rahman MT, Duti BM, Rahaman ZA, Bakshi A, Kalaivani S, Nafiz Rahaman S, Sattar GS (2023a)
Integrating forest cover change and carbon storage dynamics: leveraging Google Earth Engine and InVEST model to inform conservation in hilly regions. Ecological Indicators 152 (2): 110374.
CrossRef | Gscholar
(23)
Kafy AA, Bakshi A, Saha M, Al Faisal A, Almulhim AI, Rahaman ZA, Mohammad P (2023b)
Assessment and prediction of index based agricultural drought vulnerability using machine learning algorithms. Science of The Total Environment 867: 161394.
CrossRef | Gscholar
(24)
Kim J, Choi J, Choi C, Park S (2013)
Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea. Science of the Total Environment 452: 181-195.
CrossRef | Gscholar
(25)
Kleinhans A, Gerold G (2004)
The effects of rainforest conversion on water balance, water yield and seasonal flows in a small tropical catchment in Central Sulawesi. In: “Nature Conservation and the Stability of Rainforest Margins in Southeast Asia”. Springer, Berlin, Heidelberg, New York, pp. 353-365.
Gscholar
(26)
Krishnapillay DB, Razak MM, Appanah S (2007)
Forest rehabilitation-the Malaysian experience. Part A: status of land use and forest (and land) degradation. International Union of Forest Research Organizations.
Gscholar
(27)
LeCun Y, Bengio Y, Hinton G (2015)
Deep learning. Nature 521 (7553): 436-444.
CrossRef | Gscholar
(28)
Li Z, Liu W, Zhang X, Zheng F (2009)
Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China. Journal of Hydrology 377 (1-2): 35-42.
CrossRef | Gscholar
(29)
Mango LM, Melesse M, McClain ME, Gann D, Setegn SG (2011)
Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management. Hydrology and Earth System Sciences 15 (7): 2245-2258.
CrossRef | Gscholar
(30)
Mao D, Cherkauer K (2009)
Impacts of land-use change on hydrologic responses in the Great Lakes region. Journal of Hydrology 374 (1-2): 71-82.
CrossRef | Gscholar
(31)
Mello KD, Toppa RH, Cardoso-Leite E (2016)
Priority areas for forest conservation in an urban landscape at the transition between Atlantic Forest and Cerrado. Cerne 22: 277-288.
CrossRef | Gscholar
(32)
NC2 Project (2012)
Malaysian Second National Communication, SN Malaysia to the UNFCCC Ministry of Natural Resources and Environment Malaysia. Web site.
Online | Gscholar
(33)
Oliveira Serrão EA, Silva MT, Ferreira TR, De Ataide LCP, Dos Santos CA, De Lima AMM, Gomes DJC (2022)
Impacts of land use and land cover changes on hydrological processes and sediment yield determined using the SWAT model. International Journal of Sediment Research 37 (1): 54-69.
CrossRef | Gscholar
(34)
Rahaman ZA, Kafy AA, Faisal AA, Al Rakib A, Jahir DM, Fattah MA, Kalaivani S, Rathi R, Mallik S, Rahman MT (2022)
Predicting microscale land use/land cover changes using cellular automata algorithm on the northwest coast of peninsular Malaysia. Earth Systems and Environment 6 (4): 817-835.
CrossRef | Gscholar
(35)
Rahman K, da Silva AG, Tejeda EM, Gobiet A, Beniston M, Lehmann A (2015)
An independent and combined effect analysis of land use and climate change in the upper Rhone River watershed, Switzerland. Applied Geography 63 (2-4): 264-272.
CrossRef | Gscholar
(36)
Serpa D, Nunes JP, Santos J, Sampaio E, Jacinto R, Veiga S, Abrantes N (2015)
Impacts of climate and land use changes on the hydrological and erosion processes of two contrasting Mediterranean catchments. Science of The Total Environment 538: 64-77.
CrossRef | Gscholar
(37)
Shafie NA, Aris AZ, Puad NH (2013)
Influential factors on the levels of cation exchange capacity in sediment at Langat river. Arabian Journal of Geosciences 6 (8): 3049-3058.
CrossRef | Gscholar
(38)
Shaharudin I, Sarah Aziz AGA, Lim CS (2002)
Using geographical information systems (GIS) applications in mapping land use changes in the Langat River Basin, Selangor 1974 -2001. In: Proceedings of the “Regional Symposium on Environment and Natural Resources”. Kuala Lumpur (Malaysia) 10-11 Apr 2011, vol. 1, pp. 349-358.
Gscholar
(39)
Subedi P, Subedi K, Thapa B (2013)
Application of a hybrid cellular automaton - Markov (CA-Markov) model in land-use change prediction: a case study of Saddle Creek Drainage Basin, Florida. Applied Ecology and Environmental Sciences 1 (6): 126-132.
CrossRef | Gscholar
(40)
Taiwo BE, Kafy AA, Samuel AA, Rahaman ZA, Ayowole OE, Shahrier M, Abosede OO (2023)
Monitoring and predicting the influences of land use/land cover change on cropland characteristics and drought severity using remote sensing techniques. Environmental and Sustainability Indicators 18 (3): 100248.
CrossRef | Gscholar
(41)
Wang A, Zhang M, Kafy AA, Tong B, Hao D, Feng Y (2023)
Predicting the impacts of urban land change on LST and carbon storage using InVEST, CA-ANN and WOA-LSTM models in Guangzhou, China. Earth Science Informatics 16 (1): 437-454.
CrossRef | Gscholar
(42)
WECAM (2013)
Malaysia: flood mitigation and adaptation. Water and Energy Consumer Association of Malaysia.
Gscholar
(43)
Yang J, Entekhabi D, Castelli F, Chua L (2014)
Hydrologic response of a tropical watershed to urbanization. Journal of Hydrology 517: 538-546.
CrossRef | Gscholar
(44)
Yasin MY, Abdullah J, Yusoff MM, Mohd Noor N (2021)
The urbanization and growth of Malaysia: case study of Iskandar Region. International Journal of Social Science and Economics Invention 7 (3): 53-66.
CrossRef | Gscholar
(45)
Zhang C, Ma Y (2018)
Earth mover’s distance based neural networks for computer vision. Advances in Neural Information Processing Systems 31.
Gscholar
(46)
Zhi L, Liu W, Zhang X, Zheng F (2009)
Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China. Journal of Hydrology 377 (2009) 35-42.
Gscholar
 

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