Siva Kumar Balasundram

SWAT-based hydrological modelling of tropical land-use scenarios

Abstract The Hulu Langat basin, a strategic watershed in Malaysia, has in recent decades been exposed to extensive changes in land-use and consequently hydrological conditions. In this work, the impact of Land Use and Cover Change (LUCC) on hydrological conditions (water discharge and sediment load) of the basin were investigated using the Soil and Water Assessment Tool (SWAT). Four land-use scenarios were defined for land-use change impact analysis, i.e. past, present (baseline), future and water conservation planning. The land-use maps, dated 1984, 1990, 1997 and 2002, were defined as the past scenarios for LUCC impact analysis. The present scenario was defined based on the 2006 land-use map. The 2020 land-use map was simulated using a cellular automata-Markov model and defined as the future scenario. Water conservation scenarios were produced based on guidelines published by Malaysia’s Department of Town and Country Planning and Department of Environment. Model calibration and uncertainty analysis was performed using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The model robustness for water discharge simulation for the period 1997–2008 was good. However, due to uncertainties, mainly resulting from intense urban development in the basin, its robustness for sediment load simulation was only acceptable for the calibration period 1997–2004. The optimized model was run using different land-use maps over the periods 1997–2008 and 1997–2004 for water discharge and sediment load estimation, respectively. In comparison to the baseline scenario, SWAT simulation using the past and conservative scenarios showed significant reduction in monthly direct runoff and monthly sediment load, while SWAT simulation based on the future scenario showed significant increase in monthly direct runoff, monthly sediment load and groundwater recharge. Editor D. Koutsoyiannis; Associate editor C. Perrin

Trend analysis of water discharge and sediment load during the past three decades of development in the Langat basin, Malaysia

Abstract In this study, the trends of water discharge and sediment load from three hydrometric stations over the past 25 years of development in the state of Selangor, Peninsular Malaysia, were analysed using the Mann-Kendall and Pettitt tests. Landscape metrics for establishing the relationship between land-use changes and trends of hydrological time series were calculated. The hydrological trends were also studied in terms of rainfall variations and manmade features. The results indicate upward trends in water discharge in the Hulu Langat sub-basin and in sediment load in the Semenyih sub-basin. These increasing trends were mainly caused by rapid changes in land use. Upward trends of hydrological series in the Hulu Langat sub-basin matched its rainfall pattern. In the Lui sub-basin, however, trends of hydrological series, and variations in rainfall and land use were not statistically significant. Editor Z.W. Kundzewicz; Associate editor K. Hamed Citation Memarian, H., Balasundram, S.K., Talib, J.B., Sood, A.M., and Abbaspour, K.C., 2012. Trend analysis of water discharge and sediment load during the past three decades of development in the Langat basin, Malaysia. Hydrological Sciences Journal, 57 (6), 1207–1222.

A GIS-based model to analyze the spatial and temporal development of oil palm land use in Kuala Langat district, Malaysia

In Malaysia, areas under oil palm plantations have increased dramatically since the early twentieth century and have resulted in multiple conversions of land change. This paper presents a spatial and temporal model for simulation of oil palm expansion in the Kuala Langat district, Malaysia. The model is an integration of cellular automata (CA), multi-criteria evaluation (MCE), and Markov chain (MC) analysis while MCE provides transition rules of CA iterations and MC analysis assigns a transition probability to each single pixel at the time steps. Evaluation criteria consist of constraints and nine suitability factors indicating environmental and socio-economic issues of oil palm development. In the first simulation, changes of six land-cover classes were projected to the year 2008 based on transitions between 1997 and 2002. Two measures of quantity disagreement and allocation disagreement were adopted to validate model outcome. The simulation of land-cover change of the year 2020 was done based on the transition observed between 1997 and 2002 regarding the satisfactory agreement of the projection and the reference data at the first simulation. The results, based on five landscape metrics, indicated continuous spatial patterns of oil palm plantations but more fragmented spatial patterns of other land classes by the year 2020.

Comparison between pixel- and object-based image classification of a tropical landscape using Système Pour l’Observation de la Terre-5 imagery

Abstract Based on the Système Pour l’Observation de la Terre-5 imagery, two main techniques of classifying land-use categories in a tropical landscape are compared using two supervised algorithms: maximum likelihood classifier (MLC) and K -nearest neighbor object-based classifier. Nine combinations of scale level (SL10, SL30, and SL50) and the nearest neighbor (NN3, NN5, and NN7) are investigated in the object-based classification. Accuracy assessment is performed using two main disagreement components, i.e., quantity disagreement and allocation disagreement. The MLC results in a higher total disagreement in total landscape as compared with object-based image classification. The SL30-NN5 object-based classifier reduces allocation error by 250% as compared with the MLC. Therefore, this classifier shows a higher performance in land-use classification of the Langat basin.

Agriculture land suitability analysis evaluation based multi criteria and GIS approach

Land suitability evaluation (LSE) is a valuable tool for land use planning in major countries of the world as well as in Malaysia. However, previous LSE studies have been conducted with the use of biophysical and ecological datasets for the design of equally important socio-economic variables. Therefore, this research has been conducted at the sub national level to estimate suitable agricultural land for rubber crops in Seremban, Malaysia by application of physical variables in combination with widely employed biophysical and ecological variables. The objective of this study has been to provide an up-to date GIS-based agricultural land suitability evaluation (ALSE) for determining suitable agricultural land for Rubber crops in Malaysia. Biophysical and ecological factors were assumed to influence agricultural land use were assembled and the weights of their respective contributions to land suitability for agricultural uses were assessed using an analytic hierarchical process. The result of this study found Senawang, Mambau, Sandakan and Rantau as the most suitable areas for cultivating Rubber; whereas, Nilai and Labu are moderately suitable for growing rubber. Lenggeng, Mantin and Pantai are not suitable for growing rubber as the study foresaw potential environmental degradation of these locations from agricultural intensification. While this study could be useful in assessing the potential agricultural yields and potential environmental degradation in the study area, it could also help to estimate the potential conversion of agricultural land to non-agricultural uses.

An expert integrative approach for sediment load simulation in a tropical watershed

Prediction of highly non-linear behaviour of suspended sediment flow in rivers is of prime importance in environmental studies and watershed management. In this study, the predictive performance of artificial neural network (ANN) integrated with genetic algorithm (GA) was assessed. GA was used to optimize the parameters and architecture of the ANN. Five simulation scenarios (S1–S5) were developed using daily time series of suspended sediment discharge, water discharge, precipitation and reservoir level. The scenario S1 was composed of only water discharge input. The scenarios S2–S4 were composed of water discharge input and precipitation records at different stations. The inputs water discharge, precipitation and reservoir level formed the last scenario S5. Assessment metrics such as normalized mean square error, correlation coefficient, Nash–Sutcliffe efficiency and trend accuracy were used to evaluate the performance of ANN–GA on the simulation scenarios. Based on error analysis, differences between various scenarios in terms of error metrics were trivial, especially during the testing process. Meanwhile, S1 and S3 showed better accuracy in predicting the trend of sediment load time series, as compared to other scenarios. Based on error and sensitivity analyses, S1 with the Nash–Sutcliff efficiency and correlation coefficient of 0.56 and 0.81, respectively, was chosen as the most appropriate scenario. All networks showed a weak robustness in estimating large magnitudes of sediment load, mostly attributable to scarcity of large observed values in the training data-set. This weakness was also originated from different non-linear relationships governing the process of sediment detachment and final sediment load by a high storm event, as compared to those by low or medium storm events. Furthermore, there was an obvious sediment load overestimation in the 2008 exemplars due to a high level of daily water discharge and the outlined generalization rules. Nevertheless, ANN–GA showed reliable performance for sediment load simulation in the studied watershed.

Determination of optimum harvest maturity and non-destructive evaluation of pod development and maturity in cacao (Theobroma cacao L.) using a multiparametric fluorescence sensor: Maturity in cacao (Theobroma cacao L.) using a multiparametric fluorescence sensor

BACKGROUND A series of fluorescence indices (anthocyanin, flavonol, chlorophyll and nitrogen balance) were deployed to detect the pigments and colourless flavonoids in cacao pods of three commercial cacao (Theobroma cacao L.) genotypes (QH1003, KKM22 and MCBC1) using a fast and non-destructive multiparametric fluorescence sensor. The aim was to determine optimum harvest periods (either 4 or 5 months after pod emergence) of commercial cacao based on fluorescence indices of cacao development and bean quality. RESULTS As pod developed, cacao exhibited a rise with the peak of flavonol occurring at months 4 and 5 after pod maturity was initiated while nitrogen balance showed a decreasing trend during maturity. Cacao pods contained high chlorophyll as they developed but chlorophyll content declined significantly on pods that ripened at month 5. CONCLUSION Cacao pods harvested at months 4 and 5 can be considered as commercially-ready as the beans have developed good quality and comply with the Malaysian standard on cacao bean specification. Thus, cacao pods can be harvested earlier when they reach maturity at month 4 after pod emergence to avoid germinated beans and over fermentation in ripe pods harvested at month 5.

Research and development in agricultural robotics: A perspective of digital farming

Digital farming is the practice of modern technologies such as sensors, robotics, and data analysis for shifting from tedious operations to continuously automated processes. This paper reviews some of the latest achievements in agricultural robotics, specifically those that are used for autonomous weed control, field scouting, and harvesting. Object identification, task planning algorithms, digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming. The concepts of multi-robots, human-robot collaboration, and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming. It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information. For the case of robotic harvesting, an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators. While robots are becoming the inseparable parts of the modern farms, our conclusion is that it is not realistic to expect an entirely automated farming system in the future. Keywords: agricultural robotics, precision agriculture, virtual orchards, digital agriculture, simulation software, multi-robots DOI: 10.25165/j.ijabe.20181104.4278 Citation: Shamshiri R R, Weltzien C, Hameed I A, Yule I J, Grift T E, Balasundram S K, et al. Research and development in agricultural robotics: A perspective of digital farming. Int J Agric & Biol Eng, 2018; 11(4): 1–14.

Estimation of soil loss in Seremban, Malaysia using GIS and remote sensing technique

Runoff causes soil loss and is a continuous ecological problem in Seremban, Malaysia. It is crucial to collect data on soil loss for improved agricultural productivity and to manage natural resources effectively. This research maps the distribution and estimates the yearly mean value of soil erosion through the utilization of techniques of remote sensing and GIS by implementing the Revised Universal Soil Equation (RUSLE). To determine the variables of RUSLEs soil loss and analyze them in an integrated GIS environment, we used a scale of 1:50,000 according to criteria of topographic map, Aster Digital Elevation Model (DEM) which has a feature of spatial resolution that extends up to 20 m, a soil map which is digitally programmed with a scale of 1:250,000, and a decade of rainfall records for 12 stations. The data revealed that Seremban records an annual soil loss that ranges from no soil loss in forested areas (Lenggeng - Panti - Ampangan - Seremban) to >100 tone hectare per year in the open area ((Labu - Renggam - Lenggeng). The total annual soil loss is estimated at 883 tonnes/hectare/year and is distributed across different land cover as follows: 198 tonnes from agriculture areas, 39 tonnes from forest areas, and 20.45 from rural areas, 610 tonnes from open area, 12 tonnes from urban areas, and 1.4 tonnes from inland water areas.

Hydrological Trend Analysis Integrated with Landscape Analysis at the Watershed Scale (Case Study: Langat Basin, Malaysia)

In this study, the trends of water and sediment data collected from three hydrometer stations over the past 25 years of development in the state of Selangor, Peninsular Malaysia, were analyzed using the Mann–Kendall and Pettitt’s tests. Landscape metrics for establishing the relationship between land use changes and trends of hydrological time series were calculated. The hydrologic trends were also studied in terms of rainfall variations and man-made features. Results indicated upward trends in water discharge at the Hulu Langat sub-basin and sediment load at the Semenyih sub-basin. These increasing trends were mainly caused by rapid changes in land use. Upward trends of hydrological series at the Hulu Langat sub-basin matched its rainfall pattern. At the Lui sub-basin, however, trends of hydrological series and variations in rainfall and land use were not statistically significant.