Your search found 15 records
1 Chemin, Yann; Rabbani, U. 2011. Monitoring on-farm water storage use: from LIDAR to multi-source remote sensing. International Journal of Geoinformatics, 7(3):1-6.
Water storage ; Monitoring ; Remote sensing ; Satellite surveys ; Rain ; Surface water ; Groundwater / Australia
(Location: IWMI HQ Call no: e-copy only Record No: H044391)
(2.05 MB)
Faced with unreliable rainfall patterns, Australian farmers have developed on-farm water storage (OFS) solutions over the drought years. Recent thinking in water policy under the Commonwealth government considers extending the Cap over surface water to OFS as they are not currently covered under the Cap and eluded the effective water policy arrangements across users and the states. A unified approach to Cap implementation involving water diversions from the river system, OFS and other direct diversions and withdrawals as well as groundwater extractions is essential to enhance the scope and integrity of the Cap mechanism and bring diversions within the sustainable yield limits. This study lays ground for a detailed volume assessment calibration of each OFS within a water basin, within the prospect of using such information to enable a multi-source remote sensing monitoring system.
2 Eriyagama, Nishadi; Chemin, Yann; Amarasinghe, Upali; Alankara, Ranjith; Hoanh, Chu Thai. 2011. Estimation of consumptive water use and vulnerability mapping of coffee: a global analysis. Project report submitted to Nestle Ltd. under the project “Global Consumptive Water Use of Coffee”. Colombo, Sri Lanka: International Water Management Institute (IWMI). 43p.
Water use ; Beverages ; Coffee ; Species ; Research projects ; Mapping ; Water stress ; Water scarcity ; Water footprint ; Rainfed farming ; Irrigated farming
(Location: IWMI HQ Call no: e-copy only Record No: H044551)
(2.18 MB)
3 Chemin, Yann. 2012. A distributed benchmarking framework for actual ET models. In Irmak, A. (Ed.). Evapotranspiration - remote sensing and modeling. Rijeka, Croatia: InTech. pp.421-436.
Remote sensing ; Evapotranspiration ; Models ; Energy balance ; Soil heating ; Soil temperature ; Air temperature ; Weather data ; Data processing ; Image processing
(Location: IWMI HQ Call no: e-copy only Record No: H044675)
http://www.intechopen.com/source/pdfs/26115/InTech-A_distributed_benchmarking_framework_for_actual_et_models.pdf
https://vlibrary.iwmi.org/pdf/H044675.pdf
https://vlibrary.iwmi.org/pdf/H044675.pdf
(0.29 MB) (300.42KB)
With the various types of actual ET models being developed in the last 20 years, it becomes necessary to inter-compare methods. Most of already published ETa models comparisons address few number of models, and small to medium areas (Chemin et al., 2010; Gao & Long, 2008; García et al., 2007; Suleiman et al., 2008; Timmermans et al., 2007). With the large amount of remote sensing data covering the Earth, and the daily information available for the past ten years (i.e. Aqua/Terra-MODIS) for each pixel location, it becomes paramount to have a more complete comparison, in space and time. To address this new experimental requirement, a distributed computing framework was designed, and created. The design architecture was built from original satellite datasets to various levels of processing until reaching the requirement of various ETa models input dataset. Each input product is computed once and reused in all ETa models requiring such input. This permits standardization of inputs as much as possible to zero-in variations of models to the models internals/specificities.
4 Chemin, Yann. (Ed.) 2012. Remote sensing of planet earth. Rijeka, Croatia: InTech. 240p.
Remote sensing ; GIS ; Vegetation ; Water resources ; Surface Water ; Mapping ; Monitoring ; Wetlands ; Lakes ; Satellite surveys ; Satellite imagery ; Image analysis ; Image processing ; Data ; Analytical methods ; Time series analysis ; Land cover ; Land classification ; Land use ; Tsunamis ; Snow cover ; Models ; Environmental effects ; Water vapour / Brazil / China / Italy / Indonesia / Thailand / Chile / Japan / Solomon Islands / Samoa Islands / Indonesia / Peruacu watershed / Tibet Plateau / Umbria / Subasio Mountain Regional Park / Banda Aceh / Phang Nga / Phuket / Tohoku / Okushiri Island / Banda Aceh
(Location: IWMI HQ Call no: IWMI Record No: H044692)
http://www.intechopen.com/books/show/title/remote-sensing-of-planet-earth
https://vlibrary.iwmi.org/pdf/H044692.pdf
https://vlibrary.iwmi.org/pdf/H044692.pdf
(28.13 MB) (28.13MB)
5 Chemin, Yann; Phuphak, S.; Asilo, S.; Hijmans, R. J. 2012. Determining spatial and temporal patterns of submergence in rice with MODIS satellite data. International Journal of Geoinformatics, 8(2):1-12.
Rice ; Crop management ; Canopy ; Remote sensing ; Satellite surveys ; Surface water ; Flooding ; Drought / Northeast Thailand / Philippines / Nueva Ecija Province
(Location: IWMI HQ Call no: e-copy only Record No: H044965)
(4.28 MB)
Rice submergence is the condition by which the water level rises above the rice crop canopy. In general, rice plant response to submergence is to elongate its shoots above the rising water level. This costs in energy and eventually has a direct impact in terms of reducing yields. A specific gene, called Sub1, when introgressed into popular rice varieties by Marker Assisted Back-crossing, nearly stops the natural elongation process and permits a given local rice variety to sustain submerged conditions for a generally recognized period of about 2 weeks. Plant breeders now look for well-identified and location-accurate submergence areas in order to disseminate such improved local rice varieties. Remote sensing is proposed to provide surface water maps at high temporal resolution, determining a percentage of occurrences of surface water for a given pixel. Occurrence is defined as the count of days of identified surface water within a given period, returned in a percentage on that period. Rice area maps and knowledge of crop calendars are proposed to add to the assessment of submergence prone areas in two study areas, the Northeastern Thailand and Nueva Ecija in North Central Philippines.
6 Chemin, Yann; Phupak, S. 2012. Spatio-temporal patterns of rice submergence in north-eastern Thailand with TERRA-MODIS. Paper presented at the 33rd Asian Conference on Remote Sensing, Pattaya, Thailand, 26-30 November 2012. 8p.
(Location: IWMI HQ Call no: e-copy only Record No: H045584)
Rice submergence is the condition by which the water level rises above the rice crop canopy. In general,rice plant response to submergence is to elongate its shoots above the rising water level. This costs in energy andeventually has a direct impact in terms of reducing yields. A specific gene, called Sub1, when introgressed intopopular rice varieties by Marker Assisted Back-crossing, nearly stops the natural elongation process and permits agiven local rice variety to sustain submerged conditions for a generally recognized period of about 2 weeks. Plantbreeders now look for well-identified and location-accurate submergence areas in order to disseminate suchimproved local rice varieties. Remote sensing is proposed to provide surface water maps at high temporalresolution, determining a percentage of occurrences of surface water for a given pixel. Occurrence is defined as thecount of days of identified surface water within a given period, returned in a percentage on that period. Rice areamaps and knowledge of crop calendars are proposed to add to the assessment of submergence prone areas in theNortheastern Thailand.
7 Chemin, Yann. 2012. Wavelet-based spatio-temporal fusion of observed rainfall with NDVI in Sri Lanka. Paper presented at the 33rd Asian Conference on Remote Sensing, Pattaya, Thailand, 26-30 November 2012. 11p.
Rain ; Water management ; Time series analysis ; Remote sensing ; Vegetation index ; Meteorological stations / Sri Lanka / Hingurakgoda
(Location: IWMI HQ Call no: e-copy only Record No: H045585)
http://www.academia.edu/1953778/Wavelet-based_spatio-temporal_fusion_of_observed_rainfall_with_NDVI_in_Sri_Lanka
https://vlibrary.iwmi.org/pdf/H045585.pdf
https://vlibrary.iwmi.org/pdf/H045585.pdf
(0.38 MB)
Availability of rainfall time-series is limited in many parts of the World, and the continuity of such records is variable. This research endeavors to extend actual daily rainfall observations to ungauged areas, taking into account events of rainfall as well as cumulative total daily rainfall, over a period of 11 years. Results show that rainfall events histograms can be reconstructed, and that total cumulative rainfall is estimated with 85% accuracy, using a surrounding network of rain gauges at 30-50 Km of distance from the point of study. This research can strengthen various types of research and applications such as ungauged basins research, regional climate modeling, food security early warning systems, agricultural insurance systems, etc.
8 Alexandridis, T. K.; Panagopoulos, A.; Galanis, G.; Alexiou, I.; Cherif, I.; Chemin, Yann; Stavrinos, E.; Bilas, G.; Zalidis, G. C. 2014. Combining remotely sensed surface energy fluxes and GIS analysis of groundwater parameters for irrigation system assessment. Irrigation Science, 32(2):127-140. [doi: https://doi.org/10.1007/s00271-013-0419-8]
Remote sensing ; GIS ; Groundwater ; Water supply ; Irrigation water ; Irrigation systems ; Assessment ; Energy ; Data ; Water availability ; Water accounting ; Indicators / Greece / Tyrnavos Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046208)
(0.88 MB)
Despite being necessary for effective water management, the assessment of an irrigation system requires a large amount of input data for the estimation of related parameters and indicators, which are seldom measured in a regular and reliable manner. In this work, spatially distributed surface energy balance fluxes and geographical information systems analysis of multiple groundwater parameters were used to estimate water availability, supply, and demand, in order to calculate water-accounting indicators. This methodology was used to evaluate the performance of an irrigation system in the Pinios river basin (Greece) at two selected years of high and low water availability. Time series of archived satellite images and groundwater measurements have been used for past years to support comparative analyses, due to the limited availability of actual water measurements. The resulting maps from the proposed methodology show that the performance of the irrigation system varied across space and time due to differences in its characteristics and changes in its operation, driven by fluctuation of water availability and the response of stakeholders to water depletion. Irrigation districts with unsustainable water management were identified and, together with those with slow and/or limited groundwater recharge, were brought to the attention of water managers. The observed differences in the system operation between the wet and dry years were attributed not only to the hydrological conditions of each year, but also to the changing behaviour of farmers and the improvement actions of the water managers.
9 Eriyagama, Nishadi; Chemin, Yann; Alankara, Ranjith. 2014. A methodology for quantifying global consumptive water use of coffee for sustainable production under conditions of climate change. Journal of Water and Climate Change, 5(2):128-150.
Climate change ; Coffee industry ; Water use ; Crop yield ; Water scarcity ; Water stress ; Water management ; Irrigation
(Location: IWMI HQ Call no: e-copy only Record No: H046249)
(1.30 MB) (1 MB)
Coffee is the second most traded commodity in the world after oil. A sustainable coffee industry is crucial to maintaining global agriculture, trade, human and environmental well-being, and livelihoods. With increasing water scarcity and a changing climate, understanding and quantifying the risks associated with water, a primary input in coffee production, is vital. This methodological paper examines the means of quantifying: (a) ‘current’ consumptive water use (CWU) of green coffee (coffee beans at harvest time) globally; (b) coffee ‘hot spots’ and ‘bright spots’ with respect to levels of CWU, yields and water stress; and (c) possible impacts of climate change on the CWU of coffee. The methodology employs satellite-derived monthly evapotranspiration data, and climate projections from two global circulation models for three future scenarios. Initial estimates suggest that currently (on average) 18.9 m3/kg of water is consumed in producing one unit of green coffee. The same estimate for irrigated coffee is 8.6 m3/kg, while that for rain fed coffee is 19.6 m3/kg. Climate scenarios show that effective mean annual rainfall in many major coffee areas may decrease by the 2050s. The generic methodology presented here may be applied to other crops, too, if crop data are available.
10 Ali, S. S.; Mehmood, H.; Chemin, Yann. 2014. BMP implementations in Himalayan context: can a locally-calibrated SWAT assessment direct efforts? International Journal of Geoinformatics, 10(2):53-62.
Land degradation ; Land use ; Land cover ; Erosion ; Models ; Runoff ; Watersheds ; Calibration ; Vegetation ; River basins ; GIS / Asia / Pakistan / Mansehra / Himalayan Watersheds / Siran River
(Location: IWMI HQ Call no: e-copy only Record No: H046510)
http://journals.sfu.ca/ijg/index.php/journal/article/download/377/233
https://vlibrary.iwmi.org/pdf/H046510.pdf
https://vlibrary.iwmi.org/pdf/H046510.pdf
(4.07 MB) (4.7 MB)
Soil erosion due to accelerating runoff in various land cover types pose a serious threat to the long term sustainability of the fragile Himalayan landscape characterized by subsistence farming. Delimitation of high runoff zones, fostering soil erosion in the agricultural dominated watersheds is thus a necessity for watershed managers, NGO’s, urban planners, policy makers, and municipal administrations. The approach is practical, SWAT is a straightforward modeling system using GIS information. The BMP is also a very practical approach to mitigation of runoff accumulation on sub basin. A set of interviews with people familiar to the issues locally strengthened the confidence in the results. Results from this research show that terraces can reduce storm water runoff very effectively. There is a huge difference in amount of runoff after terraces are added to the simulation. Results showed a reduction of 57% in runoff volume during August 2004. If the area near the river is preserved as a buffer strip and a tree cover is maintained around it then it minimizes the effect surface runoff. The effect of riparian buffer is modeled in SWAT and the results show about 6% decrease in surface runoff when a buffer of 500 m is applied around the main river only. This study has drawn a location map of BMP implementations of most meaningful impact for the rehabilitation and safeguard of rivers, streams, lakes and wetlands around the river Siran in the Mansehra Tehsil, Pakistan.
11 Lacombe, Guillaume; Douangsavanh, S.; Vogel, R. M.; McCartney, Matthew; Chemin, Yann; Rebelo, Lisa-Maria; Sotoukee, Touleelor. 2014. Multivariate power-law models for streamflow prediction in the Mekong Basin. Journal of Hydrology: Regional Studies, 2:35-48. [doi: https://doi.org/10.1016/j.ejrh.2014.08.002]
River basins ; Stream flow ; Water resources ; Catchment areas ; Rain ; Drainage ; Land cover ; Models / South East Asia / Mekong Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046640)
http://www.sciencedirect.com/science/article/pii/S2214581814000226/pdf?md5=0a53266de35fd719967a25ed004835bc&pid=1-s2.0-S2214581814000226-main.pdf
https://vlibrary.iwmi.org/pdf/H046640.pdf
https://vlibrary.iwmi.org/pdf/H046640.pdf
(0.88 MB) (898.20 KB)
Study region: Increasing demographic pressure and economic development in the Mekong Basin result in greater dependency on river water resources and increased vulnerability to streamflow variations.
Study focus: Improved knowledge of flow variability is therefore paramount, especially in remote catchments, rarely gauged, and inhabited by vulnerable populations. We present simple multivariate power-law relationships for estimating streamflow metrics in ungauged areas, from easily obtained catchment characteristics. The relations were derived from weighted least square regression applied to streamflow, climate, soil, geographic, geomorphologic and land-cover characteristics of 65 gauged catchments in the Lower Mekong Basin. Step-wise and best subset regressions were used concurrently to maximize the prediction R-squared computed by leave-one-out cross-validations, thus ensuring parsimonious, yet accurate relationships.
New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%). A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.
Study focus: Improved knowledge of flow variability is therefore paramount, especially in remote catchments, rarely gauged, and inhabited by vulnerable populations. We present simple multivariate power-law relationships for estimating streamflow metrics in ungauged areas, from easily obtained catchment characteristics. The relations were derived from weighted least square regression applied to streamflow, climate, soil, geographic, geomorphologic and land-cover characteristics of 65 gauged catchments in the Lower Mekong Basin. Step-wise and best subset regressions were used concurrently to maximize the prediction R-squared computed by leave-one-out cross-validations, thus ensuring parsimonious, yet accurate relationships.
New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%). A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.
12 Lacombe, Guillaume; Douangsavanh, Somphasith; Vogel, R.; McCartney, Matthew; Chemin, Yann; Rebelo, Lisa-Maria; Sotoukee, Touleelor. 2014. Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only] Paper presented at the International Conference on Sustainability in the Water-Energy-Food Nexus, Bonn, Germany, 19-20 May 2014. pp.59.
Water resources ; Risk management ; Statistical methods ; Models ; River basins ; Catchment areas / South East Asia / Mekong Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046736)
https://publications.iwmi.org/pdf/H046736.pdf
http://wef-conference.gwsp.org/fileadmin/WEF_Conference/Conference_Programme_Sustainability_in_the_W-E-F_Nexus_web_version.pdf
http://wef-conference.gwsp.org/fileadmin/WEF_Conference/Conference_Programme_Sustainability_in_the_W-E-F_Nexus_web_version.pdf
(0.18 MB)
Increasing demographic pressure, economic development and resettlement policies in the Lower Mekong Basin induce greater population dependency on river flow to satisfy growing domestic and agricultural water demands. This dependency is particularly tight in upland areas where alternative water resources (groundwater) are scarce. As a result, communities tend to live closer to rivers, and so are more vulnerable to floods. This situation requires improved knowledge of flow variability for better management of water resources and risks. Unfortunately, stream flow measurements are scarce, especially in remote areas inhabited by the poorest and most vulnerable populations. Several water resource models have been developed to simulate and predict flows in the Lower Mekong Basin. However, most of these models have been designed to predict flow along the Mekong mainstream, precluding accurate assessments in headwater catchments. In most cases, their complexity and lack of transparency restricts potential users to modelling experts, and largely excludes those practitioners working closely with affected populations. The most integrated and informative way to characterize flow, at a specific location on a river, is to compute a flow duration curve which provides the percentage of time (duration) any particular flow is exceeded over a historical period. Using hydro-meteorological records from more than 60 gauged catchments in the Lower Mekong Basin, and a 90-meter digital elevation model, we used multiple linear regressions to develop power-law models predicting flow duration curves. These simple equations allow assessment of low, medium and high flow metrics, at any point on rivers in the Lower Mekong Basin, using easily determined geomorphological and climate characteristics. We believe that this parsimonious, transparent and highly predictive tool (89% <R2< 95%) can be used by a wide range of practitioners working in the fields of livelihood, water infrastructure engineering and agriculture.
13 Chemin, Yann; Sanjaya, Niroshan; Liyanage, Panni Kankanamlage Nirosha Chandani. 2014. An open source hardware and software online raingauge for real-time monitoring of rainwater harvesting in Sri Lanka. In Lanka Rain Water Harvesting Forum. Proceedings of the 11th Symposium on Mainstreaming Rainwater Harvesting as a Water Supply Option, Colombo, Sri Lanka, 5 September 2014. Colombo, Sri Lanka: Lanka Rain Water Harvesting Forum. pp.13-19.
Rain ; Water harvesting ; Monitoring ; Meteorological stations ; Information technology ; Software ; Climate change / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H046858)
(0.32 MB)
14 Chemin, Yann. 2016. A new methodology for virtual water level Gauges. International Journal of Geoinformatics, 12(1):15-25.
Virtual water ; Water levels ; Water storage ; Water balance ; Lakes ; Reservoir storage ; Energy generation ; Calibration ; Monitoring
(Location: IWMI HQ Call no: e-copy only Record No: H047547)
(4.57 MB)
Monitoring water stored in lakes and reservoirs is much needed in various countries for energy generation, food security and mitigating floods, among recurrent global issues. Natural and human-made open water bodies do not all have monitoring systems, this lack of regular information generates uncertainties in modeling, and increases unaccounted time-bound residuals in water balances. A large amount of water bodies storage variations are not monitored around the World. Here we show that this can be changed by the creation and the implementation of the concept of water Level Virtual Gauges (wLVGs) based on slope tracks upstream of water bodies, correlated to publicly available satellite remote sensing information returning water levels bi-monthly on average, sometimes weekly. An operational RMSE is found to be 12-52 cm height, depending on the characteristics of the upstream slopes used to calibrate wLVGs. This methodology is simple enough to be implemented for all medium to large reservoirs, but is alsofound successful for smaller rural reservoirs in tropical/sub-tropical countries. We anticipate that this can open globally distributed pathways to monitor open water bodies across the World, improve public databases on water storages and give management information for non/less-monitored water bodies.
15 Rocchini, D.; Petras, V.; Petrasova, A.; Chemin, Yann; Ricotta, C.; Frigeri, A.; Landa, M.; Marcantonio, M.; Bastin, L.; Metz, M.; Delucchi, L.; Neteler, M. 2017. Spatio-ecological complexity measures in GRASS GIS. Computers & Geosciences, 104:166-176. [doi: https://doi.org/10.1016/j.cageo.2016.05.006]
(Location: IWMI HQ Call no: e-copy only Record No: H047914)
Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes.
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