scholarly journals Estimating and validating basin-scale actual evapotranspiration using MODIS images and hydrologic models

2012 ◽  
Vol 43 (1-2) ◽  
pp. 156-166 ◽  
Author(s):  
Xiuqin Fang ◽  
Liliang Ren ◽  
Qiongfang Li ◽  
Xiaofan Liu ◽  
Fei Yuan ◽  
...  

An algorithm for estimating daily spatial actual evapotranspiration (ET) from remotely sensed MODIS data is presented. It is based on the surface energy balance scheme and the modified Priestley–Taylor equation, and has been applied to the MODIS data acquired during growing seasons over the Laohahe River basin, northeastern China. Spatial distributed mapping of daily ET for 22 clear sky days in the year of 2000 from MODIS images over the study area were obtained. In order to validate ET values estimated from MODIS data, regional daily ET values were calculated using the lumped modified Xinanjiang hydrologic model and distributed SWAT model based on the water balance scheme, respectively. The relationship between actual daily ET estimated from MODIS images and basin-scale ET calculated from the hydrologic model were in good agreement with acceptable correlation coefficient. The results suggested that the algorithm is applicable and operational for estimating and mapping basin-scale distributed daily actual ET over the study area. In order to use the algorithm proposed by this paper for water resource management and agricultural decision making, the algorithm should be validated using more data and be tested under different environment and different land use scenario conditions in future work.

2017 ◽  
Vol 21 (2) ◽  
pp. 879-896 ◽  
Author(s):  
Tirthankar Roy ◽  
Hoshin V. Gupta ◽  
Aleix Serrat-Capdevila ◽  
Juan B. Valdes

Abstract. Daily, quasi-global (50° N–S and 180° W–E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.


2021 ◽  
Author(s):  
Sophia Eugeni ◽  
Eric Vaags ◽  
Steven V. Weijs

<p>Accurate hydrologic modelling is critical to effective water resource management. As catchment attributes strongly influence the hydrologic behaviors in an area, they can be used to inform hydrologic models to better predict the discharge in a basin. Some basins may be more difficult to accurately predict than others. The difficulty in predicting discharge may also be related to the complexity of the discharge signal. The study establishes the relationship between a catchment’s static attributes and hydrologic model performance in those catchments, and also investigates the link to complexity, which we quantify with measures of compressibility based in information theory. </p><p>The project analyzes a large national dataset, comprised of catchment attributes for basins across the United States, paired with established performance metrics for corresponding hydrologic models. Principal Component Analysis (PCA) was completed on the catchment attributes data to determine the strongest modes in the input. The basins were clustered according to their catchment attributes and the performance within the clusters was compared. </p><p>Significant differences in model performance emerged between the clusters of basins. For the complexity analysis, details of the implementation and technical challenges will be discussed, as well as preliminary results.</p>


2019 ◽  
Vol 11 (4) ◽  
pp. 980-991 ◽  
Author(s):  
Aidi Huo ◽  
Xiaofan Wang ◽  
Yan Liang ◽  
Cheng Jiang ◽  
Xiaolu Zheng

Abstract The likelihood of future global water shortages is increasing and further development of existing operational hydrologic models is needed to maintain sustainable development of the ecological environment and human health. In order to quantitatively describe the water balance factors and transformation relations, the objective of this article is to develop a distributed hydrologic model that is capable of simulating the surface water (SW) and groundwater (GW) in irrigation areas. The model can be used as a tool for evaluating the long-term effects of water resource management. By coupling the Soil and Water Assessment Tool (SWAT) and MODFLOW models, a comprehensive hydrological model integrating SW and GW is constructed. The hydrologic response units for the SWAT model are exchanged with cells in the MODFLOW model. Taking the Heihe River Basin as the study area, 10 years of historical data are used to conduct an extensive sensitivity analysis on model parameters. The developed model is run for a 40-year prediction period. The application of the developed coupling model shows that since the construction of the Heihe reservoir, the average GW level in the study area has declined by 6.05 m. The model can accurately simulate and predict the dynamic changes in SW and GW in the downstream irrigation area of Heihe River Basin and provide a scientific basis for water management in an irrigation district.


2021 ◽  
Vol 14 ◽  
pp. 1-16
Author(s):  
Haris Prasanchum

The climate change and insufficient data of the discharge and sediment yield in the catchment system are the main cause of the conflict amongst the consumers. The application of a semi-distributed hydrologic model and geographic information system can be a solution to this conflict. This study implemented the SWAT model to estimate the discharge and sediment yield in the Huay Luang Catchment, Northeast of Thailand. The accuracy of the model was affirmed and compared with the data from the Kh103 observed station during 2008–2016 via SWAT-CUP. The study outcome suggested that the SWAT model provided favourable results compared to the observed data where R2, NSE, and PBIAS of the discharge were 0.79, 0.77, and -18.1% respectively and those of the sediment yield were 0.68, 0.65, and -22.7% respectively. Additionally, the quantitative analysis on 22 sub-catchments as the spatial map derived from the Watershed Delineation indicated that both discharge and sediment yield during 2008–2011 were higher than the regular values by 35.9% and 109.6% consecutively, whereas during 2012–2015 were lower than the regulars by 22.4% and 45.4%. In the raining season, more than 50% of the sub-catchments demonstrated 9–20 cubic meter per second of the discharge and 1,000–5,000 tons of the sediment yield, while during the drought season, both volumes in most of the catchments indicated less than 6 cubic meter per second and 1,000 tons, respectively. These happened due to the changes of the rainfall each year. Hopefully, the result and spatial information from this study could be a great contribution to the water resource management and development in any catchment with insufficient data.


Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1389
Author(s):  
Mohammad M. Hasan ◽  
Courtenay Strong ◽  
Adam K. Kochanski ◽  
Steven J. Burian ◽  
Michael E. Barber

The performance of dynamically downscaled climate fields with respect to observed historical stream runoff has been assessed at basin scale using a physically distributed hydrologic model (DHSVM). The dynamically downscaled climate fields were generated by running the Weather Research & Forecasting (WRF) model at 4-km horizontal resolution with boundary conditions derived from the Climate Forecast System Reanalysis. Six hydrologic models were developed using DHSVM for six mountainous tributary watersheds of the Jordan River basin at hourly time steps and 30-m spatial resolution. The size of the watersheds varies from 19 km2 to 130 km2. The models were calibrated for a 6-year period from water year (WY) 1999–2004, using the observed meteorological data from the nearby Snow Telemetry (SNOTEL) sites of the Natural Resources Conservation Services (NRCS). Calibration results showed a very good fit between simulated and observed streamflow with an average Nash-Sutcliffe Efficiency (NSE) greater than 0.77, and good to very good fits in terms of other statistical parameters like percent bias (PBIAS) and coefficient of determination (R2). A 9-year period (WY 2001–2009) was selected as the historical baseline, and stream discharges for this period were simulated using dynamically downscaled climate fields as input to the calibrated hydrologic models. Historical baseline results showed a satisfactory fit of simulated and observed streamflow with an average NSE greater than 0.45 and a coefficient of determination above 0.50. Using volumetric analysis, it has been found that the total volume of water simulated using downscaled climate projections for the entire historical baseline period for all six watersheds is 4% less than the observed amount representing a very good estimation in terms of percent error volume (PEV). However, in the case of individual watersheds, analysis of total annual water volumes showed that estimated total annual water volumes were higher than the observed for Big Cottonwood, City Creek, Millcreek and lower than the observed total annual volume of water for Little Cottonwood, Red Butte Creek, and Parleys Littledell, demonstrating similar characteristics obtained from the calibration results. Seasonal analysis showed that the models can capture the flow volume observed for Big Cottonwood, City Creek and Red Butte Creek during the peak season, and the models can capture the flow volume observed for all the watershed satisfactorily except Big Cottonwood during the dry season. Study results indicated that the dynamically downscaled climate projections used in this study performed satisfactorily in terms of stream runoff, total flow volume, and seasonal flow analyses based on different statistical tests, and can satisfactorily capture flow patterns and flow volume for most of the watersheds considering the uncertainties associated with the study.


2012 ◽  
Vol 31 ◽  
pp. 23-30 ◽  
Author(s):  
K. Bieger ◽  
G. Hörmann ◽  
N. Fohrer

Abstract. Hydrological modeling poses a particular challenge in data scarce regions, which are often subject to dynamic change and thus of specific interest to hydrological modeling studies. When a small amount of data available for a catchment is opposed by extensive data requirements by the chosen hydrologic model, ways have to be found to extract as much information from the available data as possible. In a study conducted in the Xiangxi Catchment in the Three Gorges Region in China, the use of residual analysis as well as auto- and cross-correlations for enhanced model evaluation and for the identification of key processes governing the hydrological behavior of the catchment prior to model calibration was tested. The residuals were plotted versus various variables such as time, discharge and precipitation. Also, auto-correlations were calculated for measured and simulated discharge and cross-correlations of measured and simulated discharge with precipitation were analyzed. Results show that the analysis of residuals as well as auto- and cross-correlations can provide valuable information about the catchment response to rainfall events, which can be very helpful for calibration of hydrologic models in data scarce regions.


1970 ◽  
Vol 1 (3) ◽  
pp. 181-205 ◽  
Author(s):  
ERIK ERIKSSON

The term “stochastic hydrology” implies a statistical approach to hydrologic problems as opposed to classic hydrology which can be considered deterministic in its approach. During the International Hydrology Symposium, held 6-8 September 1967 at Fort Collins, a number of hydrology papers were presented consisting to a large extent of studies on long records of hydrological elements such as river run-off, these being treated as time series in the statistical sense. This approach is, no doubt, of importance for future work especially in relation to prediction problems, and there seems to be no fundamental difficulty for introducing the stochastic concepts into various hydrologic models. There is, however, some developmental work required – not to speak of educational in respect to hydrologists – before the full benefit of the technique is obtained. The present paper is to some extent an exercise in the statistical study of hydrological time series – far from complete – and to some extent an effort to interpret certain features of such time series from a physical point of view. The material used is 30 years of groundwater level observations in an esker south of Uppsala, the observations being discussed recently by Hallgren & Sands-borg (1968).


Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1313
Author(s):  
George Akoko ◽  
Tu Hoang Le ◽  
Takashi Gomi ◽  
Tasuku Kato

The soil and water assessment tool (SWAT) is a well-known hydrological modeling tool that has been applied in various hydrologic and environmental simulations. A total of 206 studies over a 15-year period (2005–2019) were identified from various peer-reviewed scientific journals listed on the SWAT website database, which is supported by the Centre for Agricultural and Rural Development (CARD). These studies were categorized into five areas, namely applications considering: water resources and streamflow, erosion and sedimentation, land-use management and agricultural-related contexts, climate-change contexts, and model parameterization and dataset inputs. Water resources studies were applied to understand hydrological processes and responses in various river basins. Land-use and agriculture-related context studies mainly analyzed impacts and mitigation measures on the environment and provided insights into better environmental management. Erosion and sedimentation studies using the SWAT model were done to quantify sediment yield and evaluate soil conservation measures. Climate-change context studies mainly demonstrated streamflow sensitivity to weather changes. The model parameterization studies highlighted parameter selection in streamflow analysis, model improvements, and basin scale calibrations. Dataset inputs mainly compared simulations with rain-gauge and global rainfall data sources. The challenges and advantages of the SWAT model’s applications, which range from data availability and prediction uncertainties to the model’s capability in various applications, are highlighted. Discussions on considerations for future simulations such as data sharing, and potential for better future analysis are also highlighted. Increased efforts in local data availability and a multidimensional approach in future simulations are recommended.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1511
Author(s):  
Jung-Ryel Choi ◽  
Il-Moon Chung ◽  
Se-Jin Jeung ◽  
Kyung-Su Choo ◽  
Cheong-Hyeon Oh ◽  
...  

Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite high water supply ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92, 0.84, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.


1996 ◽  
Vol 21 (3) ◽  
pp. 211-218 ◽  
Author(s):  
A. Limaye ◽  
Erik B. Kluzek ◽  
Gail E. Bingham ◽  
J.P. Riley

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