scholarly journals Evaluation and application of alternative rainfall data sources for forcing hydrologic models in the Mara Basin

2017 ◽  
Vol 49 (4) ◽  
pp. 1271-1282 ◽  
Author(s):  
Tadesse Alemayehu ◽  
Fidelis Kilonzo ◽  
Ann van Griensven ◽  
Willy Bauwens
Keyword(s):  
Assessment Tool ◽  
Meteorological Data ◽  
Poor Performance ◽  
Rainfall Data ◽  
Rainfall Regime ◽  
Hydrologic Models ◽  
Climate Forecast System Reanalysis ◽  
Daily Streamflow ◽  
Basin Scale ◽  
Spatially Distributed

Abstract Accurate and spatially distributed rainfall data are crucial for a realistic simulation of the hydrological processes in a watershed. However, limited availability of observed hydro-meteorological data often challenges the rainfall–runoff modelling efforts. The main goal of this study is to evaluate the Climate Forecast System Reanalysis (CFSR) and Water and Global Change (WATCH) rainfall by comparing them with gauge observations for different rainfall regimes in the Mara Basin (Kenya/Tanzania). Additionally, the skill of these rainfall datasets to simulate the observed streamflow is assessed using the Soil and Water Assessment Tool (SWAT). The daily CFSR and WATCH rainfall show a poor performance (up to 52% bias and less than 0.3 correlation) when compared with gauge rainfall at grid and basin scale, regardless of the rainfall regime. However, the correlations for both CFSR and WATCH substantially improve at monthly scale. The 95% prediction uncertainty (95PPU) of the simulated daily streamflow, as forced by CFSR and WATCH rainfall, bracketed more than 60% of the observed streamflows. We however note high uncertainty for the high flow regime. Yet, the monthly and annual aggregated CFSR and WATCH rainfall can be a useful surrogate for gauge rainfall data for hydrologic application in the study area.

scholarly journals Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 996 ◽  
Author(s):  
Limin Zhang ◽  
Xianyong Meng ◽  
Hao Wang ◽  
Mingxiang Yang ◽  
Siyu Cai
Keyword(s):  
Northeast China ◽  
Assessment Tool ◽  
Meteorological Data ◽  
Swat Model ◽  
Poor Performance ◽  
Runoff Simulation ◽  
Reanalysis Dataset ◽  
Climate Forecast System Reanalysis ◽  
Maximum Minimum ◽  
Better Than

Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.

scholarly journals Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure

2021 ◽  
Vol 13 (4) ◽  
pp. 2375
Author(s):  
Sangchul Lee ◽  
Junyu Qi ◽  
Hyunglok Kim ◽  
Gregory W. McCarty ◽  
Glenn E. Moglen ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Assessment Tool ◽  
Spatial Scales ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Hydrologic Models ◽  
Daily Streamflow ◽  
Model Predictions ◽  
Improved Model ◽  
Water Assessment

There is a certain level of predictive uncertainty when hydrologic models are applied for operational purposes. Whether structural improvements address uncertainty has not well been evaluated due to the lack of observational data. This study investigated the utility of remotely sensed evapotranspiration (RS-ET) products to quantitatively represent improvements in model predictions owing to structural improvements. Two versions of the Soil and Water Assessment Tool (SWAT), representative of original and improved versions, were calibrated against streamflow and RS-ET. The latter version contains a new soil moisture module, referred to as RSWAT. We compared outputs from these two versions with the best performance metrics (Kling–Gupta Efficiency [KGE], Nash-Sutcliffe Efficiency [NSE] and Percent-bias [P-bias]). Comparisons were conducted at two spatial scales by partitioning the RS-ET into two scales, while streamflow comparisons were only conducted at one scale. At the watershed level, SWAT and RSWAT produced similar metrics for daily streamflow (NSE of 0.29 and 0.37, P-bias of 1.7 and 15.9, and KGE of 0.47 and 0.49, respectively) and ET (KGE of 0.48 and 0.52, respectively). At the subwatershed level, the KGE of RSWAT (0.53) for daily ET was greater than that of SWAT (0.47). These findings demonstrated that RS-ET has the potential to increase prediction accuracy from model structural improvements and highlighted the utility of remotely sensed data in hydrologic modeling.

scholarly journals Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

2014 ◽  
Vol 18 (2) ◽  
pp. 539-557 ◽  
Author(s):  
C. L. Shope ◽  
G. R. Maharjan ◽  
J. Tenhunen ◽  
B. Seo ◽  
K. Kim ◽  
...  
Keyword(s):  
Plant Growth ◽  
Assessment Tool ◽  
Meteorological Data ◽  
Swat Model ◽  
Extreme Environments ◽  
Flow Distribution ◽  
Capture Event ◽  
Growth Metrics ◽  
Spatially Distributed ◽  
Hydrologic Partitioning

Abstract. Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall–runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

scholarly journals A Review of SWAT Model Application in Africa

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1313
Author(s):  
George Akoko ◽  
Tu Hoang Le ◽  
Takashi Gomi ◽  
Tasuku Kato
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Data Availability ◽  
Mitigation Measures ◽  
Model Parameterization ◽  
Basin Scale

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.

Linking atmospheric and hydrologic models at the basin scale

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

scholarly journals Little Ice Age (Neoglacial) Paleoenvironmental Conditions At Siple Station, Antarctica

1990 ◽  
Vol 14 ◽  
pp. 199-204 ◽  
Author(s):  
Ellen Mosley-Thompson ◽  
Lonnie G. Thompson ◽  
Pieter M. Grootes ◽  
N. Gundestrup
Keyword(s):  
Little Ice Age ◽  
Regional Differences ◽  
Meteorological Data ◽  
Ice Core ◽  
Observational Evidence ◽  
Ice Age ◽  
Temperature Pattern ◽  
South Pole ◽  
Atmospheric Conditions ◽  
Spatially Distributed

The 550-year records of δ18O and dust concentrations from Siple Station, Antarctica suggest warmer and less dusty atmospheric conditions from 1600 to 1830 A.D. which encompasses much of the northern hemisphere Little Ice Age (LIA). Dust and δ18O data from South Pole Station indicate that the opposite conditions (e.g. cooler and more dusty) were prevalent there during the LIA. Meteorological data from 1945–85 show that the LIA temperature opposition between Amundsen-Scott and Siple, inferred from δ18O, is consistent with the present spatial distribution of surface temperature. There is some observational evidence suggesting that under present conditions stronger zonal westerlies produce a temperature pattern similar to that of the LIA. These regional differences demonstrate that a suite of spatially distributed, high resolution ice-core records will be necessary to characterize the LIA in Antarctica

scholarly journals Evaluation of the Performance of CFSR Reanalysis Data Set for Estimating Potential Evapotranspiration (PET) in Turkey

2021 ◽  
Author(s):  
AHMET IRVEM ◽  
Mustafa OZBULDU
Keyword(s):  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Actual Evapotranspiration ◽  
Observation Data ◽  
Reanalysis Dataset ◽  
Data Set ◽  
Climate Forecast System Reanalysis ◽  
Mountainous Regions ◽  
Weather Stations

Abstract Evapotranspiration is an important parameter for hydrological, meteorological and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, Potential Evapotranspiration (PET) is typically calculated using meteorological data to calculate actual evapotranspiration. However, it is very difficult to get complete and accurate data from meteorology stations in, rural and mountainous regions. This study examined the availability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations in the computation of potential annual and seasonal evapotranspiration. The PET calculations using the CFSR reanalysis dataset for the period 1987-2017 were compared to data observed at 259 weather stations observed in Turkey. As a result of the assessments, it was determined that the seasons in which the CFSR reanalysis data set had the best prediction performance were the winter (C'= 0.76 and PBias = -3.77) and the autumn (C' = 0.75 and PBias = -12.10). The worst performance was observed for the summer season. The performance of the annual prediction was determined as C'= 0.60 and PBias = -15.27. These findings indicate that the results of the PET calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used especially in the summer models.

scholarly journals Use of decision Tables to Simulate Management in Ecohydrological Models

2018 ◽  
Author(s):  
Jeffrey G. Arnold ◽  
Katrin Bieger ◽  
Michael J. White ◽  
Raghavan Srinivasan ◽  
John A. Dunbar ◽  
...  
Keyword(s):  
Water Stress ◽  
Land Management ◽  
Assessment Tool ◽  
Swat Model ◽  
Regulated River ◽  
Irrigation Application ◽  
Reservoir Models ◽  
Basin Scale ◽  
Rule Sets ◽  
Decision Tables

Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river-reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+) model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily NSE (Nash-Sutcliffe Efficiency) of 0.52 and a percent bias of -1.1%. Using decision tables to simulate management in land, river and reservoir models was shown to have several advantages over current approaches including: 1) mature technology with considerable literature and applications, 2) ability to accurately represent complex, real world decision making, 3) code that is efficient, modular and easy to maintain, and 4) tables that are easy to maintain, support, and modify.

scholarly journals Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 594 ◽  
Author(s):  
Majid Fereidoon ◽  
Manfred Koch ◽  
Luca Brocca
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Monthly Runoff

Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.

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