Your search found 39 records
1 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.
2 Chattopadhyay, S.; Jain, R.; Chattopadhyay, G. 1990. Estimating potential evapotranspiration from limited weather data over Gangetic West Bengal, India: a neurocomputing approach. Meteorological Applications, 16(3):405-411. [doi: https://doi.org/10.1002/met.138]
Evapotranspiration ; Monsoon climate ; Weather data ; Weather ; Models / India / Gangetic West Bengal
(Location: IWMI HQ Call no: e-copy only Record No: H045065)
(0.15 MB)
This paper reports the development of a neurocomputing-based model for estimating the potential evapotranspiration over Gangetic West Bengal, India during the summer monsoon months of June, July and August. An artificial neural network is implemented in the form of multilayer perceptron to generate the model. Three weather variables, surface temperature, vapour pressure and rainfall are used as the independent variables in generating the model. The performance of the model is judged statistically against non-linear regression in the form of asymptotic regression. The study reveals that an artificial neural network is more efficient than the regression approach to estimate the potential evapotranspiration in the summer monsoon months. Furthermore, it is established that the artificial neural network and non-linear regression have almost equal efficiency in the previously mentioned estimation in the month of June. However, in July and August the higher values of correlation and Willmott’s indices, and lower values of estimation error, indicate that the artificial neural network is more reliable than the non-linear regression approach. Since evapotranspiration is one of the basic components of the hydrological cycle and is essential for estimating irrigation water requirement, an efficient estimation procedure may help in agrometeorological modelling and irrigation scheduling in the summer monsoon months, which are of high importance for agriculture in the study zone.
3 Luo, Y.; Jiang, Y.; Peng, S.; Khan, S.; Cai, Xueliang; Wang, W.; Jiao, X. 2012. Urban weather data to estimate reference evapotranspiration for rural irrigation management. Journal of Irrigation and Drainage Engineering, 138(9):837-842. [doi: https://doi.org/10.1061/(ASCE)IR.1943-4774.0000470]
Irrigation management ; Irrigation requirements ; Weather data ; Temperature ; Humidity ; Wind speed ; Evapotranspiration ; Rural areas / China / Kaifeng Station / Huibei Station
(Location: IWMI HQ Call no: PER Record No: H045719)
(0.94 MB)
Weather data measured in urban areas are generally more easily available than those in rural areas. If the urban weather data are used to calculate the reference crop evapotranspiration (ET0) for rural irrigation management or spatial and temporal trend analysis, the results may be biased because of the differences in weather variables. We collected daily data for mean, maximum, and minimum temperatures; relative humidity; average wind speed; and sunshine duration from two stations: Kaifeng Station in the City of Kaifeng and Huibei Station in the nearby irrigation scheme for 1984–2009. ET0 for both stations were calculated using the FAO-56 Penman-Monteith method and then compared. The results indicated that the difference in daily ET0 was remarkable [with relative error (RE) of 52.6%], the difference between monthly average ET0 increased gradually during the last three decades and the temporal trends in annual average daily ET0 were opposite. There were significant differences in ETC (with RE of 31.1%) and irrigation requirements (with RE of 24.3%) between the two stations. Even though the distance between the two stations is only 20 km, the urban weather cannot be used to estimate ET0 for rural irrigation management.
4 Sood, Aditya; Muthuwatta, Lal; McCartney, Matthew. 2013. A SWAT evaluation of the effect of climate change on the hydrology of the Volta River Basin. Water International, 38(3):297-311. [doi: https://doi.org/10.1080/02508060.2013.792404]
Climate change ; Rain ; Temperature ; Hydrology ; River basins ; Flow discharge ; Water yield ; Groundwater recharge ; Water storage ; Weather data ; Reservoirs ; Calibration ; Models ; Statistical methods / West Africa / Volta River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H045833)
(3.29 MB)
The SWAT (Soil and Water Assessment Tool) was used to evaluate the impacts of a climate scenario based on IPCC A1B emissions on flows in the Volta River basin in West Africa for 2021–2050 and 2071–2100, using 1983–2012 as the reference period. Overall, the simulation indicates increased variability and a decrease of up to 40% in river flow as a consequence of decreasing rainfall and increasing temperature. In particular, the analysis shows smaller absolute but greater relative changes in the hydrology of the northern (upper) part of the basin, particularly at the end of the century.
5 Fuka, D. R.; Walter, M. T.; MacAlister, C.; Degaetano, A. T.; Steenhuis, T. S.; Easton, Z. M. 2013. Using the climate forecast system reanalysis as weather input data for watershed models. Hydrological Processes, 11p. (Online first). [doi: https://doi.org/10.1002/hyp.10073]
(Location: IWMI HQ Call no: e-copy only Record No: H046177)
(1.31 MB)
Obtaining representative meteorological data for watershed-scale hydrological modelling can be difficult and time consuming. Land-based weather stations do not always adequately represent the weather occurring over a watershed, because they can be far from the watershed of interest and can have gaps in their data series, or recent data are not available. This study presents a method for using the Climate Forecast System Reanalysis (CFSR) global meteorological dataset to obtain historical weather data and demonstrates the application to modelling five watersheds representing different hydroclimate regimes. CFSR data are available globally for each hour since 1979 at a 38-km resolution. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations, especially when stations are more than 10km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling un-gauged watersheds and advancing real-time hydrological modelling.
6 Luo, Y.; Chang, X.; Peng, S.; Khan, S.; Wang, W.; Zheng, Q.; Cai, Xueliang. 2014. Short-term forecasting of daily reference evapotranspiration using the Hargreaves–Samani model and temperature forecasts. Agricultural Water Management, 136:42-51. [doi: https://doi.org/10.1016/j.agwat.2014.01.006]
Weather forecasting ; Models ; Weather data ; Meteorological stations ; Evapotranspiration ; Temperature / China
(Location: IWMI HQ Call no: e-copy only Record No: H046345)
(3.51 MB)
Accurate daily reference evapotranspiration (ET0) forecasting is necessary for real-time irrigation forecasting. We proposed a method for short-term forecasting of ET0 using the locally calibrated Hargreaves–Samani model and temperature forecasts. Daily meteorological data from four stations in China for the period 2001–2013 were collected to calibrate and validate the Hargreaves–Samani (HS) model against the Penman–Monteith (PM) model, and the temperature forecasts for a 7-day horizonin 2012–2013 were collected and entered into the calibrated HS model to forecast the ET0. The pro-posed method was tested through comparisons between ET0 forecasts and ET0calculated from observed meteorological data and the PM model. The correlation coefficients between observed and forecasted temperatures for all stations were all greater than 0.94, and the accuracy of the minimum temperature forecast (error within ±2 C) ranged from 60.48% to 76.29% and the accuracy of the maximum tempera-ture forecast ranged from 50.18% to 62.94%. The accuracy of the ET0 forecast (error within ±1.5 mm day-1) ranged from 77.43% to 90.81%, the average values of the mean absolute error ranged from 0.64 to1.02 mm day-1, the average values of the root mean square error ranged from 0.87 to 1.36 mm day-1,and the average values of the correlation coefficient ranged from 0.64 to 0.86. The sources of errors were the error in the temperature forecasts and the fact that the effects of wind speed and relative humidity were not considered in the HS model. The applications illustrated that the proposed method could provide daily ET0forecasts with a certain degree of accuracy for real-time irrigation forecasts.
7 Sadras, V. O.; Cassman, K. G.; Grassini, P.; Hall, A. J.; Bastiaanssen, W. G. M.; Laborte, A. G.; Milne, A. E.; Sileshi, G.; Steduto, P. 2015. Yield gap analysis of field crops: methods and case studies. Rome, Itlay: FAO. (FAO Water Reports 41)
Yield gap ; Field crops ; Crop yield ; Cropping systems ; Environmental effects ; Water productivity ; Water availability ; Weather data ; Rainfed farming ; Irrigation systems ; Maize ; Rice ; Grain legumes ; Quinoa ; Nitrogen fertilizers ; Soil fertility ; Remote sensing ; Case studies / Argentina / Africa South of Sahara / India / China / USA / Southeast Asia / Zimbabwe / Bolivia
(Location: IWMI HQ Call no: 631.558 G000 SAD Record No: H047614)
(5.72 MB)
8 Haile, Alemseged Tamiru; Tefera, F. T.; Rientjes, T. 2016. Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data. International Journal of Applied Earth Observation and Geoinformation, 52:475-484. [doi: https://doi.org/10.1016/j.jag.2016.06.021]
Weather forecasting ; Weather data ; River basins ; Precipitation ; Satellite observation ; Flooding ; Rainfall-runoff relationships ; Early warning systems ; International waters ; Tributaries ; Calibration ; Models / Nigeria / Cameroon / Makurdi / Niger River / Benue River / Chadda River / Tchadda
(Location: IWMI HQ Call no: e-copy only Record No: H047675)
Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for MediumRange Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1–6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.
9 Liaqat, U. W.; Awan, U. K.; McCabe, M. F.; Choi, M. 2016. A geo-informatics approach for estimating water resources management components and their interrelationships. Agricultural Water Management, 178:89-105. [doi: https://doi.org/10.1016/j.agwat.2016.09.010]
Water resources ; Water management ; GIS ; Remote sensing ; Groundwater extraction ; Groundwater recharge ; Water supply ; Water use ; Water requirements ; Water scarcity ; Crops ; Evapotranspiration ; Irrigation schemes ; Irrigation canals ; Surface water ; Energy balance ; Models ; Weather data ; Satellite surveys ; Spatial distribution / Pakistan / Indus Basin / Hakra Canal
(Location: IWMI HQ Call no: e-copy only Record No: H047849)
(4.67 MB)
A remote sensing based geo-informatics approach was developed to estimate water resources management (WRM) components across a large irrigation scheme in the Indus Basin of Pakistan. The approach provides a generalized framework for estimating a range of key water management variables and provides a management tool for the sustainable operation of similar schemes globally. A focus on the use of satellite data allowed for the quantification of relationships across a range of spatial and temporal scales. Variables including actual and crop evapotranspiration, net and gross irrigation, net and gross groundwater use, groundwater recharge, net groundwater recharge, were estimated and then their interrelationships explored across the Hakra Canal command area. Spatially distributed remotely sensed estimates of actual evapotranspiration (ETa) rates were determined using the Surface Energy Balance System (SEBS) model and evaluated against ground-based evaporation calculated from the advection-aridity method. Analysis of ETa simulations across two cropping season, referred to as Kharif and Rabi, yielded Pearson correlation (R) values of 0.69 and 0.84, Nash-Sutcliffe criterion (NSE) of 0.28 and 0.63, percentage bias of -3.85% and 10.6% and root mean squared error (RMSE) of 10.6 mm and 12.21 mm for each season, respectively. For the period of study between 2008 and 2014, it was estimated that an average of 0.63 mm day-1 water was supplied through canal irrigation against a crop water demand of 3.81 mm day-1. Approximately 1.86 mm day-1 groundwater abstraction was estimated in the region, which contributed to fulfil the gap between crop water demand and canal water supply. Importantly, the combined canal, groundwater and rainfall sources of water only met 70% of the crop water requirements. As such, the difference between recharge and discharge showed that groundwater depletion was around -115 mm year-1 during the six year study period. Analysis indicated that monthly changes in ETa were strongly correlated (R = 0.94) with groundwater abstraction and rainfall, with the strength of this relationship significantly (p < 0.01 and 0.05) impacted by cropping seasons and land use practices. Similarly, the net groundwater recharge showed a good positive correlation (R) of 0.72 with rainfall during Kharif, and a correlation of 0.75 with canal irrigation during Rabi, at a significance level of p < 0.01. Overall, the results provide insight into the interrelationships between key WRM components and the variation of these through time, offering information to improve the management and strategic planning of available water resources in this region.
10 Shrestha, N. K.; Qamer, F. M.; Pedreros, D.; Murthy, M. S. R.; Wahid, S. M.; Shrestha, M. 2017. Evaluating the accuracy of Climate Hazard Group (CHG) satellite rainfall estimates for precipitation based drought monitoring in Koshi Basin, Nepal. Journal of Hydrology: Regional Studies, 13:138-151. [doi: https://doi.org/10.1016/j.ejrh.2017.08.004]
Meteorological observations ; Satellite observation ; Drought ; Rain ; Monitoring techniques ; Evaluation ; Precipitation ; Weather data ; Estimation ; Meteorological stations ; Mountains ; River basins / Nepal / Koshi Basin
(Location: IWMI HQ Call no: e-copy only Record No: H048329)
http://www.sciencedirect.com/science/article/pii/S2214581817300563/pdfft?md5=a0555e8065605f69522a60b59a4520d2&pid=1-s2.0-S2214581817300563-main.pdf
https://vlibrary.iwmi.org/pdf/H048329.pdf
https://vlibrary.iwmi.org/pdf/H048329.pdf
(1.64 MB) (1.64 MB)
Study region: Koshi basin, Nepal.
Study focus: While rainfall estimates based on satellite measurements are becoming a very attractive option, they are characterized by non-negligible biases. As such, we assessed the accuracy of two satellite products of the Climate Hazard Group (CHG) – (a) a satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) product, and (b) a CHIRP blended with ground-based station data (CHIRPS) – at a monthly time scale from 1981 to 2010 in the Koshi basin of Nepal using ground-based measurements. A separate analysis was also made for the data set after 1992, as the number of stations used in the blending has significantly reduced since 1992. Next, both CHG data sets were used to calculate one of the most popularly-used precipitation-based drought indicators – the Standardized Precipitation Index (SPI).
New hydrological insights for the study region: The accuracy of the CHG data set was found to be better in low-lying regions, while it was worse in higher-elevation regions. While the CHIRPS data set was better for the whole period, the CHIRP data set was found to be better for the period after 1992. Physiographic region-wise bias correction has improved the accuracy of the CHG products significantly, especially in higher-elevation regions. In terms of SPI values, the two CHG data sets indicated different drought severity when considering the whole period. However, the SPI values, and hence the drought severity were comparable when using the data from after 1992.
Study focus: While rainfall estimates based on satellite measurements are becoming a very attractive option, they are characterized by non-negligible biases. As such, we assessed the accuracy of two satellite products of the Climate Hazard Group (CHG) – (a) a satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) product, and (b) a CHIRP blended with ground-based station data (CHIRPS) – at a monthly time scale from 1981 to 2010 in the Koshi basin of Nepal using ground-based measurements. A separate analysis was also made for the data set after 1992, as the number of stations used in the blending has significantly reduced since 1992. Next, both CHG data sets were used to calculate one of the most popularly-used precipitation-based drought indicators – the Standardized Precipitation Index (SPI).
New hydrological insights for the study region: The accuracy of the CHG data set was found to be better in low-lying regions, while it was worse in higher-elevation regions. While the CHIRPS data set was better for the whole period, the CHIRP data set was found to be better for the period after 1992. Physiographic region-wise bias correction has improved the accuracy of the CHG products significantly, especially in higher-elevation regions. In terms of SPI values, the two CHG data sets indicated different drought severity when considering the whole period. However, the SPI values, and hence the drought severity were comparable when using the data from after 1992.
11 Muthuwatta, Lal; Perera, H. P. T. W.; Eriyagama, Nishadi; Surangika, Upamali K. B. N.; Premachandra, W. W. 2017. Trend and variability of rainfall in two river basins in Sri Lanka: an analysis of meteorological data and farmers’ perceptions. Water International, 12p. (Online first) [doi: https://doi.org/10.1080/02508060.2017.1406784]
Climate change adaptation ; Weather data ; River basins ; Rain ; Farmers ; Wet season / Sri Lanka / Medawachchiy / Mahailluppallama / Maradankadawala / Mihintale / Murunkan / Vavuniya / Malwathu Oya / Kalu Ganga
(Location: IWMI HQ Call no: e-copy only Record No: H048451)
Selected rainfall characteristics derived by analyzing observed rainfall data in two Sri Lankan river basins (Malwathu Oya and Kalu Ganga) were compared with the perceptions of farmers. The rainfall characteristics used for this analysis are trends, onset and cessation dates, length of the growing period, number of rainy days, and length of the dry spell. Farmers’ perceptions of changes in those characteristics were collected through household surveys. The majority of farmers in both river basins failed to recognize the long-term upward trend in annual rainfall. They also failed to describe the adaptation measures they were currently practising.
12 Amarnath, Giriraj; Simons, G. W. H.; Alahacoon, Niranga; Smakhtin, V.; Sharma, Bharat; Gismalla, Y.; Mohammed, Y.; Andrie, M. C. M. 2018. Using smart ICT to provide weather and water information to smallholders in Africa: the case of the Gash River Basin, Sudan. Climate Risk Management, 22:52-66. [doi: https://doi.org/10.1016/j.crm.2018.10.001]
Irrigation methods ; Flood irrigation ; Flooded land ; Remote sensing ; Geographical information systems ; Weather forecasting ; Weather data ; Smallholders ; River basins ; Information and Communication Technologies (icts) ; Crop production ; Crop yield ; Monitoring ; Water use ; Biomass ; Farmers ; Rain ; Case studies / Africa / Sudan / Gash River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H048976)
In the Gash Delta of Eastern Sudan, spate irrigation (flood-recession farming) contributes substantially to rural livelihoods by providing better yields than rainfed dryland farming. However, spate irrigation farmers are challenged by the unpredictability of flooding. In recent decades, the number of farmers practicing spate irrigation has decreased, due to varying rainfall intensity and frequency, insufficient infrastructure and farmers’ limited capacity to manage such variations. One solution that may help farmers face such challenges is for them to access real-time water-related information by using smart Information and Communication a Technology (ICT). This paper shows how integrating remote sensing, Geographical Information Systems (GIS), flood-forecasting models and communication platforms can, in near real time, alert smallholder farmers and relevant government departments about incoming floods, using the Gash basin of Sudan as an example. The Ministry of Water Resources of Sudan used the findings of this study to transform farmers’ responses to flood arrival from being ‘reactive’, to planning for the flood event. Intensive on-site and institutional efforts to build the capacity of farmers, farmer organizations, development departments and officers of the Ministry helped to develop the initiative from simply sending ‘emergency alerts’ to enabling stakeholders to visually see the flood event unfolding in the region and to plan accordingly for storing water, operating spate-irrigation systems and undertaking cropping activities. The research, initially conducted on a 60 × 60 km site, was later extended to the entire Gash basin. The paper outlines how to develop tools that can monitor plot-specific information from satellite measurements, and supply detailed and specific information on crops, rather than providing very general statements on crop growth. Farmers are able to use such tools to optimize their farm profits by providing water to their crops in the right place, at the right time and in the right quantity. Finally, the work demonstrates the high potential of combining technology, namely remote sensing data and simple a agro-meteorological model with limited parameters, for large-scale monitoring of spate irrigation systems and information sharing to advise farmers as to how to apply this information to their managerial decisions.
13 Taraz, V. 2018. Can farmers adapt to higher temperatures?: evidence from India. World Development, 112:205-219. [doi: https://doi.org/10.1016/j.worlddev.2018.08.006]
Climate change adaptation ; Temperature ; Farmers ; Agricultural production ; Agricultural practices ; Crop yield ; Rice ; Wheat ; Sorghum ; Sugarcane ; Maize ; Groundnuts ; Weather data ; Aquifers / India
(Location: IWMI HQ Call no: e-copy only Record No: H049036)
(2.67 MB)
Projections suggest that the damages from climate change will be substantial for developing countries. Understanding the ability of households in these countries to adapt to climate change is critical in order to determine the magnitude of the potential damages. In this paper, I investigate the ability of farmers in India to adapt to higher temperatures. I use a methodology that exploits short-term weather fluctuations as well as spatial variation in long-run climate. Specifically, I estimate how damaging high temperatures are for districts that experience high temperatures more or less frequently. I find that the losses from high temperatures are lower in heat-prone districts, a result that is consistent with adaptation. However, while adaptation appears to be modestly effective for moderate levels of heat, my results suggest that adaptation to extreme heat is much more difficult. Extremely high temperatures do grave damage to crops, even in places that experience these temperature extremes regularly. The persistence of negative impacts of high temperatures, even in areas that experience high temperatures frequently, underscores the need for development policies that emphasize risk mitigation and explicitly account for climate-change-related risks.
14 Hyland, M.; Russ, J. 2019. Water as destiny - the long-term impacts of drought in sub-Saharan Africa. World Development, 115:30-45. [doi: https://doi.org/10.1016/j.worlddev.2018.11.002]
Drought ; Climate change ; Rain ; Human capital ; Living standards ; Socioeconomic environment ; Gender ; Women ; Empowerment ; Water resources ; Weather data ; Rural areas / Africa South of Sahara
(Location: IWMI HQ Call no: e-copy only Record No: H049135)
(1.21 MB)
We examine the long-term impacts of drought exposure on women born in 19 countries in sub-Saharan Africa, across four decades. We find that women who were exposed to drought conditions during their early childhood are significantly less wealthy as adults. These effects are confined to women born and raised in rural households, indicating that the impacts of rainfall are felt via changes in agricultural output. In addition to lower levels of wealth, women who experience droughts in infancy also receive fewer years of formal education and, in the case of extreme drought conditions, have reduced adult heights. Our results also suggest that drought exposure in infancy can have long-term, negative impacts on women’s empowerment. Finally, we also show that these impacts may be transmitted to the women’s offspring, with children of affected women more likely to be born at a low birth weight (weighing <2.5 kg). To our knowledge, this represents the largest study to date both geographically and over time showing a strong relationship between early life rainfall conditions and adult outcomes, and the first to show that the impacts could span generations.
15 Tessema, K. B.; Haile, Alemseged Tamiru; Amencho, N. W.; Habib, E. 2022. Effect of rainfall variability and gauge representativeness on satellite rainfall accuracy in a small upland watershed in southern Ethiopia. Hydrological Sciences Journal, 67(16):2490-2504. (Special issue: Hydrological Data: Opportunities and Barriers) [doi: https://doi.org/10.1080/02626667.2020.1770766]
Rainfall patterns ; Rain gauges ; Satellites ; Weather data ; Evaluation ; Watersheds ; Highlands ; Precipitation ; Observation ; Estimation ; Meteorological stations ; Models / Ethiopia / Southern Nations, Nationalities, and Peoples' Region (SNNPR) / Upper Gana Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H049792)
(3.30 MB)
The actual accuracy of satellite rainfall products is often unknown due to the limitation of raingauge networks. We evaluated the effect of gauge representativeness error on evaluation of rainfall estimates from the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) rainfall product. The reference data were collected using an experimental raingauge network within a small watershed of 1690 ha, which is comparable to the CHIRPS resolution. The study applied a total bias approach, decomposed into hit, missed and false biases, and an error-variance separation method to evaluate gauge representativeness error at the scale of CHIRPS pixel size, as well as modeled the spatial correlation field of daily rainfall with a three-parametric exponential model. The results indicate that the gauge representativeness error is still too large to ignore in evaluating satellite rainfall. However, it is significantly affected by sample size and caution should be exercised when the rainfall data has a small sample size.
16 Shafieiyoun, E.; Gheysari, M.; Khiadani, M.; Koupai, J. A.; Shojaei, P.; Moomkesh, M. 2020. Assessment of reference evapotranspiration across an arid urban environment having poor data monitoring system. Hydrological Processes, 34(20):4000-4016. (Online first) [doi: https://doi.org/10.1002/hyp.13851]
Evapotranspiration ; Assessment ; Arid zones ; Urban environment ; Weather data ; Monitoring ; Water requirements ; Remote sensing ; Air temperature ; Humidity ; Solar radiation ; Meteorological stations ; Models ; Sensitivity analysis / Iran Islamic Republic / Isfahan
(Location: IWMI HQ Call no: e-copy only Record No: H049952)
(23.80 MB)
Estimation of reference evapotranspiration (ET0) in urban areas is challenging but essential in arid urban climates. To evaluate ET0 in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET0. Calculated ET0 was compared with satellite-based ET0 retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET0 and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET0 differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET0 to wind speed and sunshine hours indicated a significant effect on cumulative ET0 at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET0, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET0 in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET0 to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.
17 Yassen, A. N.; Nam, W.-H.; Hong, E.-M. 2020. Impact of climate change on reference evapotranspiration in Egypt. Catena, 194:104711. (Online first) [doi: https://doi.org/10.1016/j.catena.2020.104711]
Climate change ; Evapotranspiration ; Irrigation water ; Water resources ; Water management ; Water requirements ; Meteorological stations ; Weather data ; Spatial distribution / Egypt / Nile Delta
(Location: IWMI HQ Call no: e-copy only Record No: H049957)
(4.05 MB)
Egypt is a country that is vulnerable to many of the sustainability challenges and climate change effects to which all countries around the world are struggling to respond, and the United Nations is warning that Egypt could run out of the water by the year 2025. Reference evapotranspiration is the first step in estimating crop water requirements and irrigation water management. A better understanding of trends in reference evapotranspiration is crucial for scientific management of water resources in arid and semi-arid regions. The aim of this study is to identify the spatiotemporal of annual and monthly reference evapotranspiration changes in Egypt, as evidenced by spatial distribution and temporal trends. The results showed that significant changes in spatial distribution of reference evapotranspiration have occurred in the last 35 years beginning in the 1980s. The southeastern regions, the older agricultural lands in the Nile Delta and valley, as well as the northwestern regions were most affected regions. However, the western desert showed the lowest impact from climate change. The winter season from November to February showed the lowest impact from climate change, while during the summer season, the highest significant differences occurred, especially from June to October. The last five years (2013–2017) showed a significant decrease from the previous 5 years (2008–2012) but still show a significant increase from previous periods of time (1983–2007). Hence, the western desert is more suitable for agricultural expansion. Furthermore, agricultural and irrigation activities during the summer season have to change respond to the impact of climate change on water resources management.
18 Nigussie, Likimyelesh; Haile, Alemseged Tamiru; Gowing, J.; Walker, D.; Parkin, G. 2020. Citizen science in community-based watershed management: an institutional analysis in Ethiopia. Colombo, Sri Lanka: International Water Management Institute (IWMI). 25p. (IWMI Working Paper 191) [doi: https://doi.org/10.5337/2020.207]
Watershed management ; Community involvement ; Citizen science ; Water institutions ; Hydrometeorology ; Weather data ; Climatic data ; Monitoring ; Water resources ; Water management ; Natural resources management ; Water security ; Irrigation management ; Small scale systems ; Sustainability ; Governmental organizations ; River basin institutions ; Meteorological stations ; Participatory approaches ; Stakeholders ; Data analysis ; Access to information ; Information dissemination / Ethiopia / Abbay Basin / Rift Valley Lakes Basin
(Location: IWMI HQ Call no: IWMI Record No: H050043)
(1.22 MB)
The engagement of communities (non-scientists) in the collection of reliable hydrometeorological data (a citizen science approach) has the potential to address part of the data gaps in Ethiopia. Due to the high cost of establishing and maintaining gauging stations, hydrometeorological monitoring in the country tends to focus on large river basins (> 1,000 km2) with little or no consideration of small watersheds (< 100 km2). However, hydrologic data from small watersheds are critical for two main reasons: (i) measure the impacts of watershed management interventions on water resources; and (ii) inform local development plans, such as small- and micro-scale irrigation development. Therefore, this paper examines the institutional arrangements for hydrometeorological monitoring and the practices followed by the Basin Development Authority and National Meteorology Agency in Ethiopia. It is important to investigate the possibilities of embedding a citizen science approach into the data collection systems of these two organizations, as this will help to address data gaps, particularly at micro-watershed levels. Based on the assessments, there is potential to embed the approach into the institutional structure of the Ministry of Agriculture (MoA) for hydrometeorological monitoring in micro-watersheds, due to the following reasons: (i) MoA has a high demand for hydrometeorological data from small rivers to be used for small- and micro-scale irrigation development, and for measuring the impacts of watershed development interventions on water resources; and (ii) MoA has an institutional structure from federal to community level that supports the engagement of communities in development interventions. However, effectively embedding the citizen science approach into regular monitoring of MoA depends on the clear distribution of mandates; developing legal, ethical, methodological and quality frameworks; and developing clear data sharing and incentive mechanisms involving all partners.
19 Alemu, M. L.; Worqlul, A. W.; Zimale, F. A.; Tilahun, S. A.; Steenhuis, S. 2020. Water balance for a tropical lake in the volcanic highlands: Lake Tana, Ethiopia. Water, 12(10):2737. (Special issue: Hydrology and Sedimentology of Hilly and Mountainous Landscapes) [doi: https://doi.org/10.3390/w12102737]
Water balance ; Lakes ; Rivers ; Water levels ; Runoff ; Water loss ; Evaporation ; Irrigation ; Precipitation ; Weather data ; Rain gauges ; Watersheds ; Groundwater ; Highlands ; Models / Ethiopia / Lake Tana / Blue Nile Basin
(Location: IWMI HQ Call no: e-copy only Record No: H050064)
(4.57 MB) (4.57 MB)
Lakes hold most of the freshwater resources in the world. Safeguarding these in a changing environment is a major challenge. The 3000 km2 Lake Tana in the headwaters of the Blue Nile in Ethiopia is one of these lakes. It is situated in a zone destined for rapid development including hydropower and irrigation. Future lake management requires detailed knowledge of the water balance of Lake Tana. Since previous water balances varied greatly this paper takes a fresh look by calculating the inflow and losses of the lake. To improve the accuracy of the amount of precipitation falling on the lake, two new rainfall stations were installed in 2013. The Climate Hazards Group Infrared Precipitation Version two (CHIRPS-v2) dataset was used to extend the data. After reviewing all the previous studies and together with our measurements, it was found that the period of 1990–1995 likely had the most accurate gauged discharge data. During some months in this period, the lake water balance was negative. Since the river inflow to the lake cannot be negative, water was either lost from the lake via the subsurface through faults, or the outflow measurements were systematically underestimated. Based on the evaporation rate of 1650 mm, we found that unaccounted loss was 0.6 km3 a-1, equivalent to 20 cm of water over the lake area each year. This implies the need for reliable rainfall data and improved river discharge measurements over a greater portion of the basin both entering and exiting the lake. Also, integrated hydrological and geologic investigations are needed for a better understanding of the unaccounted water losses and quantifying the amount of subsurface flow leaving the lake.
20 Campolo, J.; Guerena, D.; Maharjan, S.; Lobell, D. B. 2021. Evaluation of soil-dependent crop yield outcomes in Nepal using ground and satellite-based approaches. Field Crops Research, 260:107987. [doi: https://doi.org/10.1016/j.fcr.2020.107987]
Crop yield ; Soil deficiencies ; Estimation ; Satellite imagery ; Remote sensing ; Soil maps ; Wheat ; Farmland ; Fertilizers ; Soil quality ; Soil properties ; Smallholders ; Weather data ; Models / Nepal / Terai Region
(Location: IWMI HQ Call no: e-copy only Record No: H050190)
(5.14 MB)
Smallholder farmers face many constraints to achieving food security. Optimal soil management is often limited by a lack of accessible and accurate soil characterization, and an associated lack of soil-specific management practice recommendations. Crop yields depend on both soil quality and soil-mediated fertilizer responses. Existing research on soil-fertilizer interactions is primarily based on farm trials and/or survey data, which are resource intensive and typically restricted to local scales. High-resolution (~10-meter) remote sensing data and digital soil maps provide a low cost, scalable alternative. Here, we deploy methods based on the Sentinel satellite constellation to estimate soil and fertilizer impacts on irrigated wheat grain yields in Nepal and to inform precision soil and nutrient management recommendations. We first combine field data with Sentinel-1 and Sentinel-2 imagery to delineate wheat cropping areas for 2016–2019 with 92 % accuracy. We then estimate wheat yields at 10-meter resolution using Sentinel-2 and weather covariates based on yield models parameterized from two different methods: 1) APSIM crop model simulations and 2) ground cropcuts from 147 fields. Using a large dataset of soil samples collected by the Nepal Agricultural Research Council, we examine the linear and non-linear effects of soil properties on wheat yields. Finally, the soil maps were combined with a survey of field-level crop management data and our yield estimates to test the interaction of soil quality with fertilizer effectiveness. Our ground-calibrated satellite model predicted yields with good accuracy (R2 = 0.55), while the uncalibrated simulation-based approach had weaker but significant prediction accuracy (R2 = 0.24). We find statistically significant gains in yield of 0.9–2.4 % are possible by increasing soil organic matter and zinc from highly deficient values to optimal values of 2.2 % organic matter (OM) and 0.67 ppm zinc (Zn). Using digital soil maps of Nepal produced by the International Maize and Wheat Improvement Center (CIMMYT), we map croplands deficient in zinc (Zn < 0.66 ppm) and organic matter (OM < 2.2 %) and find that 72 % of croplands in the Nepal Terai are experiencing less than optimal levels of these nutrients. We examine the effectiveness of nitrogen and zinc fertilizers, applied in amounts ranging from 0 to 150 kg ha-1 and 0 to 15 kg ha-1 respectively, in different soil quality regimes as determined by a soil quality index informed by standard relationships between crop yields and soil properties. Yields were significantly more responsive to zinc fertilizer inputs in soils with a higher than average soil quality but responded similarly to nitrogen inputs across different soils. Effects of soil and fertilizers on the simulation-based yield estimate were generally similar but less significant than effects on ground-calibrated yields. Overall, nitrogen and zinc increased ground-calibrated yields by 0.8 and 10.4 kg ha-1 per kg of nutrient input, respectively. This research demonstrates the potential of satellite data, crop simulation, and machine learning to examine the influence of soils on yields and guide precision fertilizer use in smallholder regions.
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