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MODIS land surface temperature data (MODIS Ts) products are quantified from the earth surface’s reflected thermal infrared signal via sensors onboard the Terra and Aqua satellites. MODIS Ts products are a great value to many environmental applications but often subject to discrepancies when compared to the air temperature (Ta) data that represent the temperature measured at 2 m above the ground surface. Although they are different in their nature, the relationship between Ts and Ta has been established by many researchers. Further validation and correction on the relationship between these two has enabled the estimation of Ta from MODIS Ts products in order to overcome the limitation of Ta that can only provide data in a point form with a very limited area coverage. Therefore, this study was conducted with the objective to assess the accuracy of MODIS Ts products, i.e., MOD11A1, MOD11A2, MYD11A1, and MYD11A2 against Ta and to identify the performance of a modified Linear Scaling using a constant and monthly correction factor (LS-MBC), and Quantile Mapping Mean Bias Correction (QM-MBC) methods for lowland area of Peninsular Malaysia. Furthermore, the correction factor (CF) values for each MBC were adjusted according to the condition set depending on the different bias levels. Then, the performance of the pre- and post-MBC correction for by stations and regions analysis were evaluated through root mean square error (RMSE), percentage bias (PBIAS), mean absolute error (MAE), and correlation coefficient (r). The region dataset is obtained by stacking the air temperature (Ta_r) and surface temperature (Ts_r) data corresponding to the number of stations within the identified regions. The assessment of pre-MBC data for both 36 stations and 5 regions demonstrated poor correspondence with high average errors and percentage biases, i.e., RMSE = 3.33–5.42 °C, PBIAS = 1.36–12.07%, MAE = 2.88–4.89 °C, and r = 0.16–0.29. The application of the MBCs has successfully reduced the errors and bias percentages, and slightly increased the r values for all MODIS Ts products. All post-MBC depicted good average accuracies (RMSE and MAE < 3 °C and PBIAS between ±5%) and r between 0.18 and 0.31. In detail, for the station analysis, the LS-MBC using monthly CF recorded better performance than the LS-MBC using constant CF or the QM-MBC. For the regional study, the QM-MBC outperformed the others. This study illustrated that the proposed LS-MBC, in spite of its simplicity, managed to perform well in reducing the error and bias terms of MODIS Ts as much as the performance of the more complex QM-MBC method.
Nurul Bahari; Farrah Muharam; Zed Zulkafli; Norida Mazlan; Nor Husin. Modified Linear Scaling and Quantile Mapping Mean Bias Correction of MODIS Land Surface Temperature for Surface Air Temperature Estimation for the Lowland Areas of Peninsular Malaysia. Remote Sensing 2021, 13, 2589 .
AMA StyleNurul Bahari, Farrah Muharam, Zed Zulkafli, Norida Mazlan, Nor Husin. Modified Linear Scaling and Quantile Mapping Mean Bias Correction of MODIS Land Surface Temperature for Surface Air Temperature Estimation for the Lowland Areas of Peninsular Malaysia. Remote Sensing. 2021; 13 (13):2589.
Chicago/Turabian StyleNurul Bahari; Farrah Muharam; Zed Zulkafli; Norida Mazlan; Nor Husin. 2021. "Modified Linear Scaling and Quantile Mapping Mean Bias Correction of MODIS Land Surface Temperature for Surface Air Temperature Estimation for the Lowland Areas of Peninsular Malaysia." Remote Sensing 13, no. 13: 2589.
Good index selection is key to minimising basis risk in weather index insurance design. However, interannual, seasonal, and intra-seasonal hydroclimatic variabilities pose challenges in identifying robust proxies for crop losses. In this study, we systematically investigated 574 hydroclimatic indices for their relationships with yield in Malaysia’s irrigated double planting system, using the Muda rice granary as a case study. The responses of seasonal rice yields to seasonal and monthly averages and to extreme rainfall, temperature, and streamflow statistics from 16 years’ observations were examined by using correlation analysis and linear regression. We found that the minimum temperature during the crop flowering to the maturity phase governed yield in the drier off-season (season 1, March to July, Pearson correlation, r = +0.87; coefficient of determination, R2 = 74%). In contrast, the average streamflow during the crop maturity phase regulated yield in the main planting season (season 2, September to January, r = +0.82, R2 = 67%). During the respective periods, these indices were at their lowest in the seasons. Based on these findings, we recommend temperature- and water-supply-based indices as the foundations for developing insurance contracts for the rice system in northern Peninsular Malaysia.
Zed Zulkafli; Farrah Muharam; Nurfarhana Raffar; Amirparsa Jajarmizadeh; Mukhtar Abdi; Balqis Rehan; Khairudin Nurulhuda. Contrasting Influences of Seasonal and Intra-Seasonal Hydroclimatic Variabilities on the Irrigated Rice Paddies of Northern Peninsular Malaysia for Weather Index Insurance Design. Sustainability 2021, 13, 5207 .
AMA StyleZed Zulkafli, Farrah Muharam, Nurfarhana Raffar, Amirparsa Jajarmizadeh, Mukhtar Abdi, Balqis Rehan, Khairudin Nurulhuda. Contrasting Influences of Seasonal and Intra-Seasonal Hydroclimatic Variabilities on the Irrigated Rice Paddies of Northern Peninsular Malaysia for Weather Index Insurance Design. Sustainability. 2021; 13 (9):5207.
Chicago/Turabian StyleZed Zulkafli; Farrah Muharam; Nurfarhana Raffar; Amirparsa Jajarmizadeh; Mukhtar Abdi; Balqis Rehan; Khairudin Nurulhuda. 2021. "Contrasting Influences of Seasonal and Intra-Seasonal Hydroclimatic Variabilities on the Irrigated Rice Paddies of Northern Peninsular Malaysia for Weather Index Insurance Design." Sustainability 13, no. 9: 5207.
Rapid, accurate and inexpensive methods are required to analyze plant traits throughout all crop growth stages for plant phenotyping. Few studies have comprehensively evaluated plant traits from multispectral cameras onboard UAV platforms. Additionally, machine learning algorithms tend to over- or underfit data and limited attention has been paid to optimizing their performance through an ensemble learning approach. This study aims to (1) comprehensively evaluate twelve rice plant traits estimated from aerial unmanned vehicle (UAV)-based multispectral images and (2) introduce Random Forest AdaBoost (RFA) algorithms as an optimization approach for estimating plant traits. The approach was tested based on a farmer’s field in Terengganu, Malaysia, for the off-season from February to June 2018, involving five rice cultivars and three nitrogen (N) rates. Four bands, thirteen indices and Random Forest-AdaBoost (RFA) regression models were evaluated against the twelve plant traits according to the growth stages. Among the plant traits, plant height, green leaf and storage organ biomass, and foliar nitrogen (N) content were estimated well, with a coefficient of determination (R2) above 0.80. In comparing the bands and indices, red, Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), Red-Edge Wide Dynamic Range Vegetation Index (REWDRVI) and Red-Edge Soil Adjusted Vegetation Index (RESAVI) were remarkable in estimating all plant traits at tillering, booting and milking stages with R2 values ranging from 0.80–0.99 and root mean square error (RMSE) values ranging from 0.04–0.22. Milking was found to be the best growth stage to conduct estimations of plant traits. In summary, our findings demonstrate that an ensemble learning approach can improve the accuracy as well as reduce under/overfitting in plant phenotyping algorithms.
Farrah Muharam; Khairudin Nurulhuda; Zed Zulkafli; Mohamad Tarmizi; Asniyani Abdullah; Muhamad Che Hashim; Siti Mohd Zad; Derraz Radhwane; Mohd Ismail. UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits. Agronomy 2021, 11, 915 .
AMA StyleFarrah Muharam, Khairudin Nurulhuda, Zed Zulkafli, Mohamad Tarmizi, Asniyani Abdullah, Muhamad Che Hashim, Siti Mohd Zad, Derraz Radhwane, Mohd Ismail. UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits. Agronomy. 2021; 11 (5):915.
Chicago/Turabian StyleFarrah Muharam; Khairudin Nurulhuda; Zed Zulkafli; Mohamad Tarmizi; Asniyani Abdullah; Muhamad Che Hashim; Siti Mohd Zad; Derraz Radhwane; Mohd Ismail. 2021. "UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits." Agronomy 11, no. 5: 915.
Damage functions are widely used to determine flood losses. National and international published damage functions are often used with little scrutiny or validation at local scales; a lack of understanding that unquestionably adds uncertainty to national flood risk assessment and investment planning. This paper examines the differences in aggregate flood damage estimates based on damage functions derived locally using local surveys and questionnaires, published national sector-based damage functions and land-use based damage functions published for Malaysia in the international literature. The paper is presented in two parts: firstly, the construction of a damage function from site-specific post-event flood surveys (covering a range of building types and flood hazard variables) and secondly, the comparison of these locally derived function with available national and international functions. A 0.05 km2 residential area located in Kuala Lumpur, Malaysia, which consists of sparsely located houses was selected for the study. It was used to drive the site-specific damage function and an associated estimate of flood damage for a range of observed and modelled flood events. The results show that at higher depths, the use of the site-specific function suggest an aggregate damage of approximately twice than an estimate based on national functions but much less (less than 100%) than would be estimated based on international published functions. The paper concludes that the international published damage functions should be used with care and condition using local (where possible) or national understanding of flood damages to avoid a significant over estimation of losses.
Balqis M. Rehan; Paul Sayers; A. Ulwan M. Alayuddin; M. Fadhil M. Ghamrawi; James D. Miller; Shabir A. Kabirzad; Alexandra Kaelin; Edmund C. Penning-Rowsell; Bakti H. Basri; Victoria A. Bell; Zed Zulkafli; Elizabeth J. Stewart. Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia. 2021, 1 .
AMA StyleBalqis M. Rehan, Paul Sayers, A. Ulwan M. Alayuddin, M. Fadhil M. Ghamrawi, James D. Miller, Shabir A. Kabirzad, Alexandra Kaelin, Edmund C. Penning-Rowsell, Bakti H. Basri, Victoria A. Bell, Zed Zulkafli, Elizabeth J. Stewart. Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia. . 2021; ():1.
Chicago/Turabian StyleBalqis M. Rehan; Paul Sayers; A. Ulwan M. Alayuddin; M. Fadhil M. Ghamrawi; James D. Miller; Shabir A. Kabirzad; Alexandra Kaelin; Edmund C. Penning-Rowsell; Bakti H. Basri; Victoria A. Bell; Zed Zulkafli; Elizabeth J. Stewart. 2021. "Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia." , no. : 1.
Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.
Fadhliani Umar; Zed Zulkafli; Badronnisa Yusuf; Siti Nurhidayu. Assessment of Streamflow Simulation for a Tropical Forested Catchment Using Dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE). Water 2021, 13, 317 .
AMA StyleFadhliani Umar, Zed Zulkafli, Badronnisa Yusuf, Siti Nurhidayu. Assessment of Streamflow Simulation for a Tropical Forested Catchment Using Dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE). Water. 2021; 13 (3):317.
Chicago/Turabian StyleFadhliani Umar; Zed Zulkafli; Badronnisa Yusuf; Siti Nurhidayu. 2021. "Assessment of Streamflow Simulation for a Tropical Forested Catchment Using Dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE)." Water 13, no. 3: 317.
Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1 - considering the flexibility, modularity and portability - and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e. the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. 32 years' continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatterplot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modelling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.
Fadhliani Umar; Zed Diyana; Badronnisa Yusuf; Siti Nurhidayu. Assessment of Streamflow Simulation for a Tropical Forested Catchment using Dynamic TOPMODEL – Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE). 2020, 1 .
AMA StyleFadhliani Umar, Zed Diyana, Badronnisa Yusuf, Siti Nurhidayu. Assessment of Streamflow Simulation for a Tropical Forested Catchment using Dynamic TOPMODEL – Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE). . 2020; ():1.
Chicago/Turabian StyleFadhliani Umar; Zed Diyana; Badronnisa Yusuf; Siti Nurhidayu. 2020. "Assessment of Streamflow Simulation for a Tropical Forested Catchment using Dynamic TOPMODEL – Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE)." , no. : 1.
The study aims to evaluate the long-term changes in meteorological parameters and to quantify their impacts on water resources of the Haro River watershed located on the upstream side of Khanpur Dam in Pakistan. The climate data was obtained from the NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) for MIROC-ESM model under two Representative Concentration Pathway (RCP) scenarios. The model data was bias corrected and the performance of the bias correction was assessed statistically. Soil and Water Assessment Tool was used for the hydrological simulation of watershed followed by model calibration using Sequential Uncertainty Fitting version-2. The study is useful for devising strategies for future management of Khanpur Dam. The study indicated that in the future, at Murree station (P-1), the maximum temperature, minimum temperature and precipitation were anticipated to increase from 3.1 °C (RCP 4.5) to 4.0 °C (RCP 8.5), 3.2 °C (RCP 4.5) to 4.3 °C (RCP 8.5) and 8.6% to 13.5% respectively, in comparison to the baseline period. Similarly, at Islamabad station (P-2), the maximum temperature, minimum temperature and precipitation were projected to increase from 3.3 °C (RCP 4.5) to 4.1 °C (RCP 8.5), 3.3 °C (RCP 4.5) to 4.2 °C (RCP 8.5) and 14.0% to 21.2% respectively compared to baseline period. The streamflows at Haro River basin were expected to rise from 8.7 m3/s to 9.3 m3/s.
Saima Nauman; Zed Zulkafli; Abdul Halim Bin Ghazali; Badronnisa Yusuf. Impact Assessment of Future Climate Change on Streamflows Upstream of Khanpur Dam, Pakistan using Soil and Water Assessment Tool. Water 2019, 11, 1090 .
AMA StyleSaima Nauman, Zed Zulkafli, Abdul Halim Bin Ghazali, Badronnisa Yusuf. Impact Assessment of Future Climate Change on Streamflows Upstream of Khanpur Dam, Pakistan using Soil and Water Assessment Tool. Water. 2019; 11 (5):1090.
Chicago/Turabian StyleSaima Nauman; Zed Zulkafli; Abdul Halim Bin Ghazali; Badronnisa Yusuf. 2019. "Impact Assessment of Future Climate Change on Streamflows Upstream of Khanpur Dam, Pakistan using Soil and Water Assessment Tool." Water 11, no. 5: 1090.
The Tropical Rainfall Measuring Mission (TRMM) was the first Earth Science mission dedicated to studying tropical and subtropical rainfall. Up until now, there is still limited knowledge on the accuracy of the version 7 research product TRMM 3B42-V7 despite having the advantage of a high temporal resolution and large spatial coverage over oceans and land. This is particularly the case in tropical regions in Asia. The objective of this study is therefore to analyze the performance of rainfall estimation from TRMM 3B42-V7 (henceforth TRMM) using rain gauge data in Malaysia, specifically from the Pahang river basin as a case study, and using a set of performance indicators/scores. The results suggest that the altitude of the region affects the performances of the scores. Root Mean Squared Error (RMSE) is lower mostly at a higher altitude and mid-altitude. The correlation coefficient (CC) generally shows a positive but weak relationship between the rain gauge measurements and TRMM (0 < CC < 0.4), while the Nash-Sutcliffe Efficiency (NSE) scores are low (NSE < 0.1). The Percent Bias (PBIAS) shows that TRMM tends to overestimate the rainfall measurement by 26.95% on average. The Probability of Detection (POD) and Threat Score (TS) demonstrate that more than half of the pixel-point pairs have values smaller than 0.7. However, the Probability of False Detection (POFD) and False Alarm Rate (FAR) show that most of the pixel-point gauges have values lower than 0.55. The seasonal analysis shows that TRMM overestimates during the wet season and underestimates during the dry season. The bias adjustment shows that Mean Bias Correction (MBC) improved the scores better than Double-Kernel Residual Smoothing (DS) and Residual Inverse Distance Weighting (RIDW). The large errors imply that TRMM may not be suitable for applications in environmental, water resources, and ecological studies without prior correction.
Siti Najja Mohd Zad; Zed Zulkafli; Farrah Melissa Muharram. Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia. Remote Sensing 2018, 10, 388 .
AMA StyleSiti Najja Mohd Zad, Zed Zulkafli, Farrah Melissa Muharram. Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia. Remote Sensing. 2018; 10 (3):388.
Chicago/Turabian StyleSiti Najja Mohd Zad; Zed Zulkafli; Farrah Melissa Muharram. 2018. "Satellite Rainfall (TRMM 3B42-V7) Performance Assessment and Adjustment over Pahang River Basin, Malaysia." Remote Sensing 10, no. 3: 388.
Flood is a major disaster that happens around the world. It has caused the loss of many precious lives and destruction of large amounts of property. The possibility of flood can be determined depends on many factors that consist of rainfall, water flow rate and water level. This project aims to design a water level prediction system which is used to analyze the Kelantan River water level based on Sokor River, Galas River and Lebir River flow rate and rainfall of at Ldg. Kuala Nal and Ldg. Kenneth. The system utilizes neural networks in predicting the water level for 5 hours ahead. This system has 5 inputs and 1 output prediction. This prediction system focusses on comparing the conventional method and the Neural Network Autoregressive with Exogenous Input (NNARX) system in determining the possibility of flood. The result shows that the NNARX can predict the water level of Kelantan River much more better compared to conventional method. The performance of the system is based on the value of the means square error (MSE). The MSE of the conventional method is 0.2550 meanwhile for NNARX is 1.342 × 10 -4 .
Mohd Azrol Syafiee Anuar; Ribhan Zafira Abdul Rahman; Samsul Bahari Mohd; Azura Che Soh; Zed Zulkafli. Early prediction system using neural network in Kelantan River, Malaysia. 2017 IEEE 15th Student Conference on Research and Development (SCOReD) 2017, 104 -109.
AMA StyleMohd Azrol Syafiee Anuar, Ribhan Zafira Abdul Rahman, Samsul Bahari Mohd, Azura Che Soh, Zed Zulkafli. Early prediction system using neural network in Kelantan River, Malaysia. 2017 IEEE 15th Student Conference on Research and Development (SCOReD). 2017; ():104-109.
Chicago/Turabian StyleMohd Azrol Syafiee Anuar; Ribhan Zafira Abdul Rahman; Samsul Bahari Mohd; Azura Che Soh; Zed Zulkafli. 2017. "Early prediction system using neural network in Kelantan River, Malaysia." 2017 IEEE 15th Student Conference on Research and Development (SCOReD) , no. : 104-109.
Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru. Environmental management may involve polycentric governance arrangements.Decision support for such contexts needs to meet diverse user requirements.A user-driven approach is proposed that involves actor and decision making analysis.This is combined with co-design methods from Human-Computer Interaction research.The result is more tailored decision support for users with different experiences.
Zed Zulkafli; Katya Perez; Claudia Vitolo; Wouter Buytaert; Timothy Karpouzoglou; Art Dewulf; Bert De Bièvre; Julian Clark; David M. Hannah; Simrita Shaheed. User-driven design of decision support systems for polycentric environmental resources management. Environmental Modelling & Software 2016, 88, 58 -73.
AMA StyleZed Zulkafli, Katya Perez, Claudia Vitolo, Wouter Buytaert, Timothy Karpouzoglou, Art Dewulf, Bert De Bièvre, Julian Clark, David M. Hannah, Simrita Shaheed. User-driven design of decision support systems for polycentric environmental resources management. Environmental Modelling & Software. 2016; 88 ():58-73.
Chicago/Turabian StyleZed Zulkafli; Katya Perez; Claudia Vitolo; Wouter Buytaert; Timothy Karpouzoglou; Art Dewulf; Bert De Bièvre; Julian Clark; David M. Hannah; Simrita Shaheed. 2016. "User-driven design of decision support systems for polycentric environmental resources management." Environmental Modelling & Software 88, no. : 58-73.
Despite significant advances in the development of the ecosystem services concept across the science and policy arenas, the valuation of ecosystem services to guide sustainable development remains challenging, especially at a local scale and in data scarce regions. In this paper, we review and compare major past and current valuation approaches and discuss their key strengths and weaknesses for guiding policy decisions. To deal with the complexity of methods used in different valuation approaches, our review uses multiple entry points: data vs simulation, habitat vs system vs place-based, specific vs entire portfolio, local vs regional scale, and monetary vs non-monetary. We find that although most valuation approaches are useful to explain ecosystem services at a macro/system level, an application of locally relevant valuation approaches, which allows for a more integrated valuation relevant to decision making is still hindered by data-scarcity. The advent of spatially explicit policy support systems shows particular promise to make the best use of available data and simulations. Data collection remains crucial for the local scale and in data scarce regions. Leveraging citizen science-based data and knowledge co-generation may support the integrated valuation, while at the same time making the valuation process more inclusive, replicable and policy-oriented.
B. Pandeya; W. Buytaert; Zed Zulkafli; Timos Karpouzoglou; Feng Mao; D.M. Hannah. A comparative analysis of ecosystem services valuation approaches for application at the local scale and in data scarce regions. Ecosystem Services 2016, 22, 250 -259.
AMA StyleB. Pandeya, W. Buytaert, Zed Zulkafli, Timos Karpouzoglou, Feng Mao, D.M. Hannah. A comparative analysis of ecosystem services valuation approaches for application at the local scale and in data scarce regions. Ecosystem Services. 2016; 22 ():250-259.
Chicago/Turabian StyleB. Pandeya; W. Buytaert; Zed Zulkafli; Timos Karpouzoglou; Feng Mao; D.M. Hannah. 2016. "A comparative analysis of ecosystem services valuation approaches for application at the local scale and in data scarce regions." Ecosystem Services 22, no. : 250-259.
Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the tropical Andes. The Tropical Rainfall Measuring Mission Precipitation Radar (TPR) was active for 17 years (1998 - 2014) and has generated one of the longest single-sensor, high-resolution and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross-validation and catchment water balances (runoff ratios) for 50 catchments across the tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients, but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary kriging. Among the S-G merging methods, performance of inverse-distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g. Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.
Bastian Manz; Wouter Buytaert; Zed Zulkafli; Waldo Lavado-Casimiro; Bram Willems; Luis Alberto Robles; Juan‐Pablo Rodríguez‐Sánchez. High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes. Journal of Geophysical Research: Atmospheres 2016, 121, 1190 -1207.
AMA StyleBastian Manz, Wouter Buytaert, Zed Zulkafli, Waldo Lavado-Casimiro, Bram Willems, Luis Alberto Robles, Juan‐Pablo Rodríguez‐Sánchez. High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes. Journal of Geophysical Research: Atmospheres. 2016; 121 (3):1190-1207.
Chicago/Turabian StyleBastian Manz; Wouter Buytaert; Zed Zulkafli; Waldo Lavado-Casimiro; Bram Willems; Luis Alberto Robles; Juan‐Pablo Rodríguez‐Sánchez. 2016. "High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes." Journal of Geophysical Research: Atmospheres 121, no. 3: 1190-1207.
Developments in technologies are shaping information access globally. This presents opportunities and challenges for understanding the role of new technologies in sustainability research. This article focuses on a suite of technologies termed Environmental Virtual Observatories (EVOs) developed for communicating observations and simulation of environmental processes. A strength of EVOs is that they are open and decentralised, thus democratising flow and ownership of information between multiple actors. However, EVOs are discussed rarely beyond their technical aspects. By evaluating the evolution of EVOs, we illustrate why it is timely to engage with policy and societal aspects as well. While first generation EVOs are primed for scientists, second generation EVOs can have broader implications for knowledge co-creation and resilience through their participatory design
Timos Karpouzoglou; Zed Zulkafli; Sam Grainger; Art Dewulf; Wouter Buytaert; David Hannah. Environmental Virtual Observatories (EVOs): prospects for knowledge co-creation and resilience in the Information Age. Current Opinion in Environmental Sustainability 2016, 18, 40 -48.
AMA StyleTimos Karpouzoglou, Zed Zulkafli, Sam Grainger, Art Dewulf, Wouter Buytaert, David Hannah. Environmental Virtual Observatories (EVOs): prospects for knowledge co-creation and resilience in the Information Age. Current Opinion in Environmental Sustainability. 2016; 18 ():40-48.
Chicago/Turabian StyleTimos Karpouzoglou; Zed Zulkafli; Sam Grainger; Art Dewulf; Wouter Buytaert; David Hannah. 2016. "Environmental Virtual Observatories (EVOs): prospects for knowledge co-creation and resilience in the Information Age." Current Opinion in Environmental Sustainability 18, no. : 40-48.
The impact of a changing climate on the Amazon basin is a subject of intensive research because of its rich biodiversity and the significant role of rainforests in carbon cycling. Climate change has also a direct hydrological impact, and increasing efforts have focused on understanding the hydrological dynamics at continental and subregional scales, such as the Western Amazon. New projections from the Coupled Model Inter-comparison Project Phase 5 ensemble indicate consistent climatic warming and increasing seasonality of precipitation in the Peruvian Amazon basin. Here we use a distributed land surface model to quantify the potential impact of this change in the climate on the hydrological regime of the upper Amazon river. Using extreme value analysis, historical and future projections of the annual minimum, mean, and maximum river flows are produced for a range of return periods between 1 and 100 yr. We show that the RCP 4.5 and 8.5 scenarios of climate change project an increased severity of the wet season flood pulse (7.5% and 12% increases respectively for the 100 yr return floods). These findings agree with previously projected increases in high extremes under the Special Report on Emissions Scenarios climate projections, and are important to highlight due to the potential consequences on reproductive processes of in-stream species, swamp forest ecology, and socio-economy in the floodplain, amidst a growing literature that more strongly emphasises future droughts and their impact on the viability of the rainforest system over greater Amazonia.
Zed Zulkafli; Wouter Buytaert; Bastian Manz; Claudia Véliz Rosas; Patrick Willems; Waldo Lavado-Casimiro; Jean Loup Guyot; William Santini. Projected increases in the annual flood pulse of the Western Amazon. Environmental Research Letters 2016, 11, 014013 .
AMA StyleZed Zulkafli, Wouter Buytaert, Bastian Manz, Claudia Véliz Rosas, Patrick Willems, Waldo Lavado-Casimiro, Jean Loup Guyot, William Santini. Projected increases in the annual flood pulse of the Western Amazon. Environmental Research Letters. 2016; 11 (1):014013.
Chicago/Turabian StyleZed Zulkafli; Wouter Buytaert; Bastian Manz; Claudia Véliz Rosas; Patrick Willems; Waldo Lavado-Casimiro; Jean Loup Guyot; William Santini. 2016. "Projected increases in the annual flood pulse of the Western Amazon." Environmental Research Letters 11, no. 1: 014013.
This study compares two nonparametric rainfall data merging methods—the mean bias correction and double-kernel smoothing—with two geostatistical methods—kriging with external drift and Bayesian combination—for optimizing the hydrometeorological performance of a satellite-based precipitation product over a mesoscale tropical Andean watershed in Peru. The analysis is conducted using 11 years of daily time series from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (also TRMM 3B42) and 173 rain gauges from the national weather station network. The results are assessed using 1) a cross-validation procedure and 2) a catchment water balance analysis and hydrological modeling. It is found that the double-kernel smoothing method delivered the most consistent improvement over the original satellite product in both the cross-validation and hydrological evaluation. The mean bias correction also improved hydrological performance scores, particularly at the subbasin scale where the rain gauge density is higher. Given the spatial heterogeneity of the climate, the size of the modeled catchment, and the sparsity of data, it is concluded that nonparametric merging methods can perform as well as or better than more complex geostatistical methods, whose assumptions may not hold under the studied conditions. Based on these results, a systematic approach to the selection of a satellite–rain gauge data merging technique is proposed that is based on data characteristics. Finally, the underperformance of an ordinary kriging interpolation of the rain gauge data, compared to TMPA and other merged products, supports the use of satellite-based products over gridded rain gauge products that utilize sparse data for hydrological modeling at large scales.
Daniele Nerini; Zed Zulkafli; Li-Pen Wang; Christian Onof; Wouter Buytaert; Waldo Lavado-Casimiro; Jean Loup Guyot. A Comparative Analysis of TRMM–Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall–Runoff Modeling Applications. Journal of Hydrometeorology 2015, 16, 2153 -2168.
AMA StyleDaniele Nerini, Zed Zulkafli, Li-Pen Wang, Christian Onof, Wouter Buytaert, Waldo Lavado-Casimiro, Jean Loup Guyot. A Comparative Analysis of TRMM–Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall–Runoff Modeling Applications. Journal of Hydrometeorology. 2015; 16 (5):2153-2168.
Chicago/Turabian StyleDaniele Nerini; Zed Zulkafli; Li-Pen Wang; Christian Onof; Wouter Buytaert; Waldo Lavado-Casimiro; Jean Loup Guyot. 2015. "A Comparative Analysis of TRMM–Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall–Runoff Modeling Applications." Journal of Hydrometeorology 16, no. 5: 2153-2168.
The participation of the general public in the research design, data collection and interpretation process together with scientists is often referred to as citizen science. While citizen science itself has existed since the start of scientific practice, developments in sensing technology, data processing and visualisation, and communication of ideas and results, are creating a wide range of new opportunities for public participation in scientific research. This paper reviews the state of citizen science in a hydrological context and explores the potential of citizen science to complement more traditional ways of scientific data collection and knowledge generation for hydrological sciences and water resources management. Although hydrological data collection often involves advanced technology, the advent of robust, cheap and low-maintenance sensing equipment provides unprecedented opportunities for data collection in a citizen science context. These data have a significant potential to create new hydrological knowledge, especially in relation to the characterisation of process heterogeneity, remote regions, and human impacts on the water cycle. However, the nature and quality of data collected in citizen science experiments is potentially very different from those of traditional monitoring networks. This poses challenges in terms of their processing, interpretation, and use, especially with regard to assimilation of traditional knowledge, the quantification of uncertainties, and their role in decision support. It also requires care in designing citizen science projects such that the generated data complement optimally other available knowledge. Lastly, we reflect on the challenges and opportunities in the integration of hydrologically-oriented citizen science in water resources management, the role of scientific knowledge in the decision-making process, and the potential contestation to established community institutions posed by co-generation of new knowledge.
Wouter Buytaert; Zed Zulkafli; Sam Grainger; Luis Acosta; Tilashwork C. Alemie; Johan Bastiaensen; Bert De Biã¨vre; Jagat Bhusal; Julian Clark; Art Dewulf; Marc Foggin; David M. Hannah; Christian Hergarten; Aiganysh Isaeva; Timos Karpouzoglou; Bhopal Pandeya; Deepak Paudel; Keshav Sharma; Tammo Steenhuis; Seifu Tilahun; Gert Van Hecken; Munavar Zhumanova. Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development. Frontiers in Earth Science 2014, 2, 1 .
AMA StyleWouter Buytaert, Zed Zulkafli, Sam Grainger, Luis Acosta, Tilashwork C. Alemie, Johan Bastiaensen, Bert De Biã¨vre, Jagat Bhusal, Julian Clark, Art Dewulf, Marc Foggin, David M. Hannah, Christian Hergarten, Aiganysh Isaeva, Timos Karpouzoglou, Bhopal Pandeya, Deepak Paudel, Keshav Sharma, Tammo Steenhuis, Seifu Tilahun, Gert Van Hecken, Munavar Zhumanova. Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development. Frontiers in Earth Science. 2014; 2 ():1.
Chicago/Turabian StyleWouter Buytaert; Zed Zulkafli; Sam Grainger; Luis Acosta; Tilashwork C. Alemie; Johan Bastiaensen; Bert De Biã¨vre; Jagat Bhusal; Julian Clark; Art Dewulf; Marc Foggin; David M. Hannah; Christian Hergarten; Aiganysh Isaeva; Timos Karpouzoglou; Bhopal Pandeya; Deepak Paudel; Keshav Sharma; Tammo Steenhuis; Seifu Tilahun; Gert Van Hecken; Munavar Zhumanova. 2014. "Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development." Frontiers in Earth Science 2, no. : 1.
The Tropical Rainfall Measuring Mission 3B42 precipitation estimates are widely used in tropical regions for hydrometeorological research. Recently, version 7 of the product was released. Major revisions to the algorithm involve the radar reflectivity–rainfall rate relationship, surface clutter detection over high terrain, a new reference database for the passive microwave algorithm, and a higher-quality gauge analysis product for monthly bias correction. To assess the impacts of the improved algorithm, the authors compare the version 7 and the older version 6 products with data from 263 rain gauges in and around the northern Peruvian Andes. The region covers humid tropical rain forest, tropical mountains, and arid-to-humid coastal plains. The authors find that the version 7 product has a significantly lower bias and an improved representation of the rainfall distribution. They further evaluated the performance of the version 6 and 7 products as forcing data for hydrological modeling by comparing the simulated and observed daily streamflow in nine nested Amazon River basins. The authors find that the improvement in the precipitation estimation algorithm translates to an increase in the model Nash–Sutcliffe efficiency and a reduction in the relative bias between the observed and simulated flows by 30%–95%.
Zed Zulkafli; Wouter Buytaert; Christian Onof; Bastian Manz; Elena Tarnavsky; Waldo Lavado-Casimiro; Jean Loup Guyot. A Comparative Performance Analysis of TRMM 3B42 (TMPA) Versions 6 and 7 for Hydrological Applications over Andean–Amazon River Basins. Journal of Hydrometeorology 2014, 15, 581 -592.
AMA StyleZed Zulkafli, Wouter Buytaert, Christian Onof, Bastian Manz, Elena Tarnavsky, Waldo Lavado-Casimiro, Jean Loup Guyot. A Comparative Performance Analysis of TRMM 3B42 (TMPA) Versions 6 and 7 for Hydrological Applications over Andean–Amazon River Basins. Journal of Hydrometeorology. 2014; 15 (2):581-592.
Chicago/Turabian StyleZed Zulkafli; Wouter Buytaert; Christian Onof; Bastian Manz; Elena Tarnavsky; Waldo Lavado-Casimiro; Jean Loup Guyot. 2014. "A Comparative Performance Analysis of TRMM 3B42 (TMPA) Versions 6 and 7 for Hydrological Applications over Andean–Amazon River Basins." Journal of Hydrometeorology 15, no. 2: 581-592.
Global land surface models (LSMs) such as the Joint UK Land Environment Simulator (JULES) are originally developed to provide surface boundary conditions for climate models. They are increasingly used for hydrological simulation, for instance to simulate the impacts of land use changes and other perturbations on the water cycle. This study investigates how well such models represent the major hydrological fluxes at the relevant spatial and temporal scales – an important question for reliable model applications in poorly understood, data-scarce environments. The JULES-LSM is implemented in a 360 000 km2 humid tropical mountain basin of the Peruvian Andes–Amazon at 12-km grid resolution, forced with daily satellite and climate reanalysis data. The simulations are evaluated using conventional discharge-based evaluation methods, and by further comparing the magnitude and internal variability of the basin surface fluxes such as evapotranspiration, throughfall, and surface and subsurface runoff of the model with those observed in similar environments elsewhere. We find reasonably positive model efficiencies and high correlations between the simulated and observed streamflows, but high root-mean-square errors affecting the performance in smaller, upper sub-basins. We attribute this to errors in the water balance and JULES-LSM's inability to model baseflow. We also found a tendency to under-represent the high evapotranspiration rates of the region. We conclude that strategies to improve the representation of tropical systems to be (1) addressing errors in the forcing and (2) incorporating local wetland and regional floodplain in the subsurface representation.
Z. Zulkafli; W. Buytaert; C. Onof; Waldo Lavado-Casimiro; Jean Loup Guyot. A critical assessment of the JULES land surface model hydrology for humid tropical environments. Hydrology and Earth System Sciences 2013, 17, 1113 -1132.
AMA StyleZ. Zulkafli, W. Buytaert, C. Onof, Waldo Lavado-Casimiro, Jean Loup Guyot. A critical assessment of the JULES land surface model hydrology for humid tropical environments. Hydrology and Earth System Sciences. 2013; 17 (3):1113-1132.
Chicago/Turabian StyleZ. Zulkafli; W. Buytaert; C. Onof; Waldo Lavado-Casimiro; Jean Loup Guyot. 2013. "A critical assessment of the JULES land surface model hydrology for humid tropical environments." Hydrology and Earth System Sciences 17, no. 3: 1113-1132.
A set of 130 digital precipitation maps of the tropical Andes, covering Colombia, Ecuador and Peru at a 5km resolution. The maps represent different realizations of mean precipitation totals of the period 1981-2010 using different satellite-gauge merging methods. The work draws on a large database of 723 rain gauges and the full 5km Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) record from 1998 to 2014. Each map is approximately 1MB
B. Manz; W. Buytaert; Z. Zulkafli; W. Lavado; B. Willems; A. Robles L.; J.-P. Rodríguez Sánchez. High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes. 2021, 1 .
AMA StyleB. Manz, W. Buytaert, Z. Zulkafli, W. Lavado, B. Willems, A. Robles L., J.-P. Rodríguez Sánchez. High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes. . 2021; ():1.
Chicago/Turabian StyleB. Manz; W. Buytaert; Z. Zulkafli; W. Lavado; B. Willems; A. Robles L.; J.-P. Rodríguez Sánchez. 2021. "High-resolution satellite-gauge merged precipitation climatologies of the tropical Andes." , no. : 1.