Browsing by Author "Sawadogo, Alidou"
Now showing 1 - 5 of 5
- Results Per Page
- Sort Options
Publication Comparative analysis of the pysebal model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey(Selçuk Üniversitesi Yayınları, 2020-06-01) Sawadogo, Alidou; Tim, Hessels; Gündoğdu, Kemal Sulhi; Demir, Ali Osman; Ünlü, Mustafa; Zwart, Sander Jaap; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; DEMİR, ALİ OSMAN; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü; 0000-0002-5591-4788; 0000-0002-5091-1801; JLX-2232-2023; DXY-6494-2022; ABI-4047-2020Accurate 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 (ETa) 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 ETa estimated by the pySEBAL model and ETa 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, ETa of soybean crop can be estimated with high accuracy by the pySEBAL model in Adana, Turkey.Publication Estimating in-season actual evapotranspiration over a large-scale irrigation scheme in resource-limited conditions(Publ House Bulgarian, 2020-01-01) Sawadogo, Alidou; Gündoğdu, Kemal Sulhi; Traore, Farid; Kouadio, Louis; Hessels, Tim; Sawadogo, Alidou; GÜNDOĞDU, KEMAL SULHİ; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; 0000-0002-7437-8415; 0000-0002-5591-4788; 0000-0002-7264-7220; ABI-4047-2020; DXY-6494-2022Reliable and readily available data on actual evapotranspiration (ETa) over large-scale areas throughout the crop growing season are critical for improved agricultural irrigation and water resource management. On-site data collection is costly, labour-intensive, and very challenging in resource-limited conditions. Thus, open-source satellite-based approaches might be adopted as cost-effective alternatives. In this study, the performance of a cost-effective and open source satellite-based approach for estimating ETa over a large-scale (1200 ha) irrigation system, the Kou Valley Irrigation Scheme (KVIS), in Burkina Faso was assessed. ETa values over the critical irrigation period during the 2014 dry season (January-April) were estimated using the Python module for Surface Energy Balance Algorithm for Land model (PySEBAL). Then, they were compared against the Water Productivity Open-access (FAO-WaPOR), and United States Geological Survey-Famine Early Warning Systems Network Operational Simplified Surface Energy Balance (USGS-FEWS NET's SSEBop) ETa over the same period at different temporal scales. Overall, ETa values were satisfactorily estimated throughout the crop growth season across the Kou Valley irrigation scheme using PySEBAL. They spatially varied depending on the soil type and crop, with daily values ranging from 4.09 mm day(-1) to 7.7 mm day(-1), for a seasonal average of 619 mm. The finer spatial resolution (30 m) of PySEBAL outputs allowed better estimations compared to the FAO-WaPOR and SSEBop-based approaches. Our findings help ascertain the use of the PySEBAL model in semi-arid environment in Burkina Faso, and could serve as a basis for developing strategies for improved irrigation water management in countries experiencing similar conditions such as Burkina Faso.Publication Probabilistic yield forecasting of robusta coffee at the farm scale using agroclimatic and remote sensing derived indices(Elsevier, 2021-05-10) Kouadio, Louis; Byrareddy, Vivekananda M.; Sawadogo, Alidou; Newlands, Nathaniel K.; Sawadogo, Alidou; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü; 0000-0002-7437-8415; DXY-6494-2022Timely and reliable coffee yield forecasts using agroclimatic information are pivotal to the success of agricultural climate risk management throughout the coffee value chain. The capability of statistical models to forecast coffee yields at different lead times during the growing season at the farm scale was assessed. Using data collected during a 10-year period (2008-2017) from 558 farmers across the four major coffee-producing provinces in Vietnam (Dak Lak, Dak Nong, Gia Lai, and Lam Dong), the models were built through a robust statistical modelling approach involving Bayesian and machine learning methods. Overall, coffee yields were estimated with reasonable accuracies across the four study provinces based on agroclimate variables, satellite-derived actual evapotranspiration, and crop and farm management information. Median values of prediction mean absolute percentage error (MAPE) ranged generally from 8% to 13%, and median root mean square errors (RMSE) between 295 kg ha(-1) and 429 kg ha(-1). For forecasts at four to one month before harvest, errors did not vary markedly when comparing the median MAPE and RMSE values. For farms in Dak Lak, Dak Nong, and Lam Dong, the median forecasting MAPE and RMSE varied between 13% and 16% and between 420 kg ha(-1) and 456 kg ha(-1), respectively. Using readily and freely available data, the modelling approach explored in this study appears flexible for an application to a larger number of coffee farms across the Vietnamese coffee-producing regions. Moreover, the study can serve as basis for developing a coffee yield predicting forecasting system that will offer substantial benefits to the entire coffee industry through better supply chain management in coffee-producing countries worldwide.Item Spatiotemporal assessment of irrigation performance of the Kou Valley irrigation scheme in burkina faso using satellite remote sensing-derived indicators(MDPI, 2020-08) Kouadio, Louis; Traoré, Farid; Zwart, Sander J.; Hessels, Tim; Sawadogo, Alidou; Gündoğdu, Kemal Sulhi; Uludağ Üniversitesi/Ziraat Fakültesi/Biyosistem Mühendisliği Bölümü.; DXY-6494-2022; ABI-4047-2020; 57218880390; 12784402000Traditional methods based on field campaigns are generally used to assess the performance of irrigation schemes in Burkina Faso, resulting in labor-intensive, time-consuming, and costly processes. Despite their extensive application for such performance assessment, remote sensing (RS)-based approaches remain very much underutilized in Burkina Faso. Using multi-temporal Landsat images within the Python module for the Surface Energy Balance Algorithm for Land model, we investigated the spatiotemporal performance patterns of the Kou Valley irrigation scheme (KVIS) during two consecutive cropping seasons. Four performance indicators (depleted fraction, relative evapotranspiration, uniformity of water consumption, and crop water productivity) for rice, maize, and sweet potato were calculated and compared against standard values. Overall, the performance of the KVIS varied depending on year, crop, and the crop's geographical position in the irrigation scheme. A gradient of spatially varied relative evapotranspiration was observed across the scheme, with the uniformity of water consumption being fair to good. Although rice was the most cultivated, a shift to more sweet potato farming could be adopted to benefit more from irrigation, given the relatively good performance achieved by this crop. Our findings ascertain the potential of such RS-based cost-effective methodologies to serve as basis for improved irrigation water management in decision support tools.Item Sulama yönetiminin iyileştirilmesi için uzaktan algılama yaklaşımı ile sulama projelerinin performansının değerlendirilmesi, Burkina Faso, Kou Vadisi örneği(Bursa Uludağ Üniversitesi, 2021-07-07) Sawadogo, Alidou; Gündoğdu, Kemal Sulhi; Bursa Uludağ Üniversitesi/Fen Bilimleri Enstitüsü/Biyosistem Mühendisliği Anabilim Dalı.; 0000-0002-7437-8415İklim koşulları ile birlikte sulamada suyun randımanlı kullanımı üzerindeki baskı artmaktadır. Düzenli performans değerlendirmeleri yapmak için kaynak eksikliği göz önüne alındığında, sulama suyu yönetimini iyileştirmek ve bitkisel üretimi sürdürmek için uygun maliyetli performans değerlendirme metodolojilerinin kullanılması kritik öneme sahiptir. Çalışma alanı olarak, Burkina Faso’nun güneybatısında yer alan 1200 hektarlık Kou vadisi sulama alanı (KVIS) seçilmiş, 2013 ve 2014 yıllarının kurak mevsimleri için çalışma gerçekleştirilmiştir. KVIS sulama performansının farklılık gösterdiği, yetiştirilen bitkiye ve coğrafi konumuna bağlı olarak değiştiği gözlenmiştir. Sulama alanında konumsal bağlı kademeli olarak değişen rölatif evapotranspirasyon değeri gözlenmiştir. Su stres seviyelerine göre, iyi sulanan alandan orta seviyede sulanan alana kadar, yüksek su stresli alandan çok yüksek su stresli alanlara kadar sınıflar gözlenmiştir. Su tüketim homojenliğine göre ise, orta düzeyden iyi düzeye kadar sınıflar gözlenmiştir. Bitki su verimliliği (CWP) değeri, çalışılan iki yıl için konumsal değişiklik göstermiştir. ETa ve CWP'yi etkileyen ana fizikokimyasal faktörler ise, arazi ile ana kanal su alım noktası arasındaki mesafe (DPSI), tarla yüksekliği, kum ve silt içerikleri, toprak toplam azotu, ekstrakte edilebilir potasyum ve çinko olarak elde edilmiştir. ETa veya CWP'deki değişkenliği açıklamada DPSI en çok katkıda bulunan değişken olmuştur. Çalışma ile uzaktan algılama tabanlı metodolojilerin, veri kıtlığı ve kaynak kısıtlılığı olan sulama alanlarında, sulama suyu yönetiminin iyileştirilmesi için, karar destek araçları olarak hizmet etme potansiyeli ortaya konulmuştur.