Your search found 10 records
1 Bastiaanssen, W. G. M.; Zwart, S. J.; Pelgrum, H. 2003. Remote sensing analysis. In van Dam, J. C.; Malik, R. S. (Eds.), Water productivity of irrigated crops in Sirsa district, India: Integration of remote sensing, crop and soil models and geographical information systems. Haryana, India: Haryana Agricultural University; Colombo, Sri Lanka: International Water Management Institute (IWMI); Wageningen, Netherlands: Wageningen University; Wageningen, Netherlands: WaterWatch. pp.85-100.
Remote sensing ; Satellite surveys ; Wheat ; Rice ; Cotton ; Productivity ; Crop yield / India / Sirsa
(Location: IWMI-HQ Call no: IWMI 631.7.1 G635 VAN Record No: H033895)
(3.65MB)
2 Zwart, S. J.; Bastiaanssen, W. G. M. 2004. Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize. Agricultural Water Management, 69(2):115-133.
Irrigated farming ; Wheat ; Rice ; Cotton ; Maize ; Water scarcity ; Evapotranspiration ; Experiments
(Location: IWMI-HQ Call no: PER Record No: H035691)
3 Immerzeel, W. W.; Gaur, Anju; Zwart, S. J.. 2008. Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment. Agricultural Water Management, 95(1):11-24.
Remote sensing ; Simulation models ; Hydrology ; Water balance ; Crop production ; Productivity ; Evapotranspiration / India / Upper Bhima catchment
(Location: IWMI HQ Call no: IWMI 631.7.1 G635 IMM Record No: H041183)
4 Zwart, S. J.; Bastiaanssen, W. G. M.; de Fraiture, Charlotte; Molden, David. 2010. WATPRO: a remote sensing based model for mapping water productivity of wheat. Agricultural Water Management, 97(10):1628-1636. [doi: https://doi.org/10.1016/j.agwat.2010.05.017]
(Location: IWMI HQ Call no: e-copy only Record No: H042955)
(0.65 MB)
Water productivity in agriculture needs to be improved significantly in the coming decades to secure food supply to a growing world population. To assess on a global scale where water productivity can be improved and what the causes are for not reaching its potential, the current levels must be understood. This paper describes the development and validation of a WATer PROductivity (WATPRO) model for wheat that is based on remote sensing-derived input data sets, and that can be applied at local to global scales. The model is a combination of Monteith’s theoretical framework for dry matter production in plants and an energy balance model to assess actual evapotranspiration. It is shown that by combining both approaches, the evaporative fraction and the atmospheric transmissivity, two parameters which are usually difficult to estimate spatially, can be omitted. Water productivity can then be assessed from four spatial variables: broadband surface albedo, the vegetation index NDVI, the extraterrestrial radiation and air temperature. A sensitivity analysis revealed that WATPRO is most sensitive to changes in NDVI and least sensitive to changes in air temperature. The WATPRO model was applied at 39 locations where water productivity was measured under experimental conditions. The correlation between measured and modelled water productivity was low, and this can be mainly attributed to differences in scales and in the experimental and modelling periods. A comparison with measurements from farmer’s fields in areas surrounded by other wheat fields located in Sirsa District, NW India, showed an improved correlation. Although not a validation, a comparison with SEBAL-derived water productivity in the same region in India proved that WATPRO can spatially predict water productivity with the same spatial variation.
5 Zwart, S. J.; Bastiaanssen, W. G. M.; de Fraiture, Charlotte; Molden, David. 2010. A global benchmark map of water productivity for rainfed and irrigated wheat. Agricultural Water Management, 97(10):1617-1627. [doi: https://doi.org/10.1016/j.agwat.2010.05.018]
(Location: IWMI HQ Call no: e-copy only Record No: H042956)
(0.60 MB)
The growing pressure on fresh water resources demands that agriculture becomes more productive with its current water use. Increasing water productivity is an often cited solution, though the current levels of water productivity are not systematically mapped. A global map of water productivity helps to identify where water resources are productively used, and identifies places where improvements are possible. The WATPRO water productivity model for wheat, using remote sensing data products as input, was applied at a global scale with global data sets of the NDVI and surface albedo to benchmark water productivity of wheat for the beginning of this millennium. Time profiles of the NDVI were used to determine the time frame from crop establishment to harvest on a pixel basis, which was considered the modelling period. It was found that water productivity varies from approximately 0.2 to 1.8 kg of harvestable wheat per cubic metre of water consumed. From the 10 largest producers of wheat, France and Germany score the highest country average water productivity of 1.42 and 1.35 kg m-3, respectively. The results were compared with modelling information by Liu et al. (2007) who applied the GEPIC model at a global scale to map water productivity, and by Chapagain and Hoekstra (2004) who used FAO statistics to determine water productivity per country. A comparison with Liu et al. showed a good correlation for most countries, but the correlation with the results by Chapagain and Hoekstra was less obvious. The global patterns of the water productivity map were compared with global data sets of precipitation and reference evapotranspiration to determine the impact of climate and of water availability reflected by precipitation. It appears that the highest levels of water productivity are to be expected in temperate climates with high precipitation. Due to its non-linear relationship with precipitation, it is expected that large gains in water productivity can be made with in situ rain water harvesting or supplemental irrigation in dry areas with low seasonal precipitation. A full understanding of the spatial patterns by country or river basin will support decisions on where to invest and what measures to take to make agriculture more water productive.
6 Zwart, S. J.. 2010. Benchmarking water productivity in agriculture and the scope for improvement: remote sensing modelling from field to global scale. Thesis. Delft, Netherlands: VSSD. 102p.
Water productivity ; Models ; Remote sensing ; Wheat ; Evapotranspiration ; Irrigated farming ; Rainfed farming
(Location: IWMI HQ Call no: D 631.7.1 G000 ZWA Record No: H043107)
(0.25 MB)
7 Schmitter, Petra; Zwart, S. J.; Danvi, A.; Gbaguidi, F. 2015. Contributions of lateral flow and groundwater to the spatio-temporal variation of irrigated rice yields and water productivity in a West-African inland valley. Agricultural Water Management, 152:286-298. [doi: https://doi.org/10.1016/j.agwat.2015.01.014]
Groundwater ; Water table ; Flow discharge ; Spatial distribution ; Irrigation ; Rice ; Water productivity ; Water resources ; Water management ; Water balance ; Inland waters ; Valleys ; Crop performance ; Fertilizer application ; Soil organic matter / West Africa
(Location: IWMI HQ Call no: e-copy only Record No: H046882)
Water management techniques to elevate rice yields and productive use of water resources in Africa, frequently lack a substantial spatial assessment as they are often based on plot level measurements without taking into account toposequential effects present in the landscape. These effects have been shown to significantly affect spatio-temporal variations in water availability and rice productivity in Asia. Therefore, this study addresses the spatio-temporal variations of the various water components within irrigated toposequences in an African inland valley and assesses its effect on water productivity and respective rice yields for two irrigation practices: (i) continuous flooding (CF), a well-known water management practice in rice cultivation used worldwide and (ii) a reduced irrigation scheme (RI) where irrigation is applied every 5 days resulting in a 1–2 cm water layer after irrigation. The lateral flow observed in the inland valley had a strong two-dimensional character, contributing to water gains between fields, located at the same toposequential level as well as along toposequences. The toposequential effect on sub-surface hydrological processes masked the overall effect of water management treatment on rice production. Additionally, the associated water productivity (WP) was not found to differ significantly between the treatments when standard calculations (i.e. net irrigation and evapotranspiration) were used but a clear toposequential effect was found for the fertilized lower lying fields when the net irrigation was corrected by the lateral flow component. Results of the established mixed regression model indicated that based on the groundwater table, rainfall and standard soil physico-chemical characteristics rice yields can be predicted in these African inland valleys under continuous flooding and reduced irrigation practices. Validation of the established regression function of inland valleys, representing various groundwater tables in the region, could lead to improved regression functions suitable to estimate spatial variation in rice production and water consumption across scales as affected by water management, fertilizer application and groundwater tables.
8 Danvi, A.; Giertz, S.; Zwart, S. J.; Diekkruger, B. 2017. Comparing water quantity and quality in three inland valley watersheds with different levels of agricultural development in Central Benin. Agricultural Water Management, 192:257-270. [doi: https://doi.org/10.1016/j.agwat.2017.07.017]
Water resources ; Inland waters ; Watersheds ; Agricultural development ; Intensification ; Water quality ; Water balance ; Water budget ; Nitrates ; Hydrological factors ; Models ; Calibration ; Performance evaluation ; Uncertainty ; Environmental effects ; Discharges ; Valleys / West Africa / Benin / Kounga Watershed / Tossahou Watershed / Kpandouga Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H048316)
(2.72 MB)
Achieving sustainable agricultural intensification in inland valleys while limiting the impacts on water quantity and water quality requires a better understanding of the valleys’ hydrological behavior with respect to their contributing watersheds. This study aims at assessing the dynamics of hydrological processes and nitrate loads within inland valleys that are experiencing different land uses. To achieve this goal, an HRU-based interface (ArcSWAT2012) and a grid-based setup (SWATgrid) of the Soil Water Assessment Tool (SWAT) model were applied to three headwater inland valley watersheds located in the commune of Djougou in central Benin that are characterized by different proportions of cultivated area. Satisfactory model performance was obtained from the calibration and validation of daily discharges with the values of R2 and NSE mostly higher than 0.5, but not for nitrate loads. The annual water balance reveals that more than 60% of precipitation water is lost to evapotranspiration at all sites, amounting to 868 mm in Kounga, 741 mm in Tossahou, and 645 mm in Kpandouga. Percolation (302 mm) is important in the Kpandouga watershed which is dominated by natural vegetation at 99.7%, whereas surface runoff (105 mm) and lateral flow (92 mm) are the highest in the Kounga watershed having the highest proportion of agricultural land use (14%). In all the studied watersheds, nitrate loads are very low (not exceeding 4000 KgN per year) due to the low fertilizer application rates, and the water quality is not threatened if a standard threshold of 10 mg/l NO3-N is applied. The results achieved in this study show that SWAT can successfully be used in spatial planning for sustainable agricultural development with limited environmental impact on water resources in inland valley landscapes.
9 Busetto, L.; Zwart, S. J.; Boschetti, M. 2019. Analysing spatial-temporal changes in rice cultivation practices in the Senegal River Valley using MODIS time-series and the phenorice algorithm. International Journal of Applied Earth Observation and Geoinformation, 75:15-28. [doi: https://doi.org/10.1016/j.jag.2018.09.016]
Agricultural practices ; Rice ; Intensive cropping ; Time series analysis ; Satellite observation ; Monitoring ; Rivers ; Irrigated farming ; Estimation ; Phenology ; Moderate resolution imaging spectroradiometer / West Africa / Senegal River Valley
(Location: IWMI HQ Call no: e-copy only Record No: H049456)
(4.87 MB)
In this study we used the PhenoRice algorithm to track recent variations of rice cultivation practices along the Senegal River Valley. Time series of MODIS imagery with 250 m spatial resolution and a nominal 8-days frequency were used as input for the algorithm to map the spatial and temporal variations of rice cultivated area and of several important phenological metrics (e.g., crop establishment and harvesting dates, length of season) for the 2003–2016 period in both the dry and the wet rice cultivation seasons. Comparison between PhenoRice results and ancillary and field data available for the Senegal part of the study area showed that the algorithm is able to track the interannual variations of rice cultivated area, despite the total detected rice area being consistently underestimated. PhenoRice estimates of crop establishment and harvesting dates resulted accurate when compared with field observations available for two sub-regions for a period of 10 years, and thus allow assessing interannual variability and tracking changes in agronomic practices. An analysis of interannual trends of rice growing practices based on PhenoRice results highlighted a clear shift of rice cultivation from the wet to the dry season starting approximately from 2008. The shift was found to be particularly evident in the delta part of the SRV. Additionally, a statistically significant trend was revealed starting 2006 towards a longer dry season (r2 = 0.81; Slope = 1.24 days y-1) and a shorter wet season (r2 = 0.65; Slope = 0.53 days y-1). These findings are in agreement with expert knowledge of changes ongoing in the area. In particular the shorter wet season is attributed to shortage of labor and equipment leading to a delay in completion of harvesting operations in the dry season, which led to the adoption of short-duration rice varieties by farmers in the wet season to avoid risk of yield losses due to climatic constraints. Aforementioned results highlight the usefulness of the PhenoRice algorithm for providing insights about recent variations in rice cultivation practices over large areas in developing countries, where high-quality up to date information about changes in agricultural practices are often lacking.
10 Sawadogo, A.; Tim, H.; Gundogdu, K. S.; Demir, A. O.; Unlu, M.; Zwart, S. J.. 2020. Comparative analysis of the pysebal model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey. International Journal of Engineering and Geosciences, 5(2):060-065. (Online first). [doi: https://doi.org/10.26833/ijeg.573503]
Evapotranspiration ; Crops ; Soybeans ; Irrigation water ; Satellite imagery ; Landsat ; Remote sensing ; Models ; Lysimeters / Turkey / Adana
(Location: IWMI HQ Call no: e-copy only Record No: H049544)
(0.98 MB) (0.98 MB)
Accurate estimation of evapotranspiration (ET) is an important factor in water management, especially in irrigated agriculture. Accurate irrigation scheduling requires accurate estimation of ET. The objective of this study was to estimate the actual evapotranspiration (ET a ) by the pySEBAL model and to compare it with the actual evapotranspiration measured by the lysimeter method of soybean crop in Adana, Turkey. Five Landsat 5 Thematic Mapper (TM) images and weather data were used for this study to estimate actual evapotranspiration by the pySEBAL model . The results showed a good relationship between ET a estimated by the pySEBAL model and ET a measured by the lysimeter method , with an R 2 of 0.73, an RMSE of 0.51 mm.day -1 , an MBE of 0.04 mm.day -1 and a Willmott's index of agreement ( d ) of 0.90. Based on this study, there is a good relationship between the actual evapotranspiration estimated by the pySEBAL model and the actual evapotranspiration measured by the lysimeter method. Consequently, ET a of soybean crop can be estimated with high accuracy by the pySEBAL model in Adana, Turkey.
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