scholarly journals Validation of Three Daily Satellite Rainfall Products in a Humid Tropic Watershed, Brantas, Indonesia: Implications to Land Characteristics and Hydrological Modelling

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 154
Author(s):  
Bagus Setiabudi Wiwoho ◽  
Ike Sari Astuti ◽  
Imam Abdul Gani Alfarizi ◽  
Hetty Rahmawati Sucahyo

A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and qualitative accuracy indicators, as well as R2 and NSE from hydrological estimates, were used as the performance measures. The results show that all of the satellite estimates are unsatisfactory, giving the NRMSE ranging from 6 to 30% at a daily level, with CC only 0.21–0.36. Limited number of gauges, coarse spatial data resolution, and physical terrain complexity were found to be linked with low accuracy. Accuracy was slightly better in dry seasons or low rain rate classes. The errors increased exponentially with the increase in rain rates. CHIPRS and PERSIANN tend to slightly underestimate at lower rain rates, but do show a consistently better performance, with an NRMSE of 6–12%. CHRIPS and PERSIANN also exhibit better estimates of monthly flow data and water balance components, namely runoff, groundwater, and water yield. GPM has a better ability for rainfall event detections, especially during high rainfall events or extremes (>40 mm/day). The errors of the satellite products are generally linked to slope, wind, elevation, and evapotranspiration. Hydrologic simulations using SWAT modelling and the three satellite rainfall products show that CHIRPS slightly has the daily best performance, with R2 of 0.59 and 0.62, and NSE = 0.54, and the monthly aggregated improved at a monthly level. The water balance components generated at an annual level, using three satellite products, show that CHIRPS outperformed with a ration closer to one, though with a tendency to overestimate up to 3–4× times the data generated from the rainfall gauges. The findings of this study are beneficial in supporting efforts for improving satellite rainfall products and water resource implications.

2016 ◽  
Author(s):  
Hongwei Ruan ◽  
Songbing Zou ◽  
Zhentao Cong ◽  
Yuhan Wang ◽  
Zhenliang Yin ◽  
...  

Abstract. Precipitation stations are usually scarce and unevenly distributed in inland river basins, which restrict the application of the distributed hydrological model and spatial analysis of water balance component characteristics. This study regards the upper Heihe River Basin as a case, and daily gridded precipitation data with 3 km resolutions based on the spatial interpolation of gauged stations and the regional climate model is used to construct the soil and water assessment tool (SWAT). This study aims to validate the superiority of high-resolution gridded precipitation for hydrological simulation in data scarce regions. A scale transformation method is proposed by building virtual stations and calculating the lapse rate to overcome the defects of the SWAT model using traditional precipitation station data. The gridded precipitation is upscale from the grid to the sub-basin scale and results in accurate representation of sub-basin precipitation input data. A satisfactory runoff simulation is achieved, and the spatial variability of the water balance components is analysed. Results show that the precipitation lapse rate ranges from 40 mm/km to 235 mm/km and decreases from the southeastern to the northwestern areas; its changes trend is consistent with precipitation. The SWAT model achieves monthly runoff simulation compared with gauged runoff from 2000 to 2014; the determination coefficients are higher than 0.71, the Nash–Sutcliffe efficiencies are higher than 0.76 and the percent bias are controlled within ±15 %. The meadow and sparse vegetation are the major water yield landscapes, and the elevation band at 3,500 m to 4,500 m is the major water yield area in this basin. Precipitation and evapotranspiration presented a slightly increasing trend, whereas water yield and soil water content presented a slightly decreasing trend. This finding indicates that the high-resolution gridded precipitation data well depicts its spatial heterogeneity, and scale transformation significantly promotes the application of the distributed hydrological model in inland river basins. The spatial variability of water balance components can be quantified to provide references for the integrated assessment and management of basin water resources in data scarce regions.


This study mainly focus on hydrological behavior of watersheds in The Manjira River basin using soil and water assessment tool (SWAT) and Geographical information system (GIS). The water balance components for watersheds in the Manjira River were determined by using SWAT model and GIS. Determination of these water balance components helps to study direct and indirect factors affecting characteristics of selected watersheds. Manjira River contains total 28 watersheds among them 2 were selected having watershed code as MNJR008 and MNJR011 specified by the Central Ground Water Board. The SWAT input data such as Digital elevation model (DEM), land use and land cover (LU/LC), Soil classification, slope and weather data was collected. Using these inputs in SWAT the different water balancing components such as rainfall, baseflow, surface runoff, evapotranspiration (ET), potential evapotranspiration (PET) and water yield for each watershed were determined. The evaluated data is then validated by Regression analysis, in which two datasets were compared. Simulated rain data from SWAT simulation and observed rain data from Global Weather Data for SWAT was selected for comparison for each watershed.


Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2901
Author(s):  
Davy Sao ◽  
Tasuku Kato ◽  
Le Hoang Tu ◽  
Panha Thouk ◽  
Atiqotun Fitriyah ◽  
...  

Many calibration techniques have been developed for the Soil and Water Assessment Tool (SWAT). Among them, the SWAT calibration and uncertainty program (SWAT-CUP) with sequential uncertainty fitting 2 (SUFI-2) algorithm is widely used and several objective functions have been implemented in its calibration process. In this study, eight different objective functions were used in a calibration of stream flow of the Pursat River Basin of Cambodia, a tropical monsoon and forested watershed, to examine their influences on the calibration results, parameter optimizations, and water resources estimations. As results, many objective functions performed better than satisfactory in calibrating the SWAT model. However, different objective functions defined different fitted values and sensitivity rank of the calibrated parameters, except Nash–Sutcliffe efficiency (NSE) and ratio of standard deviation of observations to root mean square error (RSR) which are equivalent and produced quite identical simulation results including parameter sensitivity and fitted parameter values, leading to the same water balance components and water yields estimations. As they generated reasonable fitted parameter values, either NSE or RSR gave better estimation results of annual average water yield and other water balance components such as annual average evapotranspiration, groundwater flow, surface runoff, and lateral flow according to the characteristics of the river basin and the results and data of previous studies. Moreover, either of them was also better in calibrating base flow, falling limb, and overall the entire flow phases of the hydrograph in this area.


2020 ◽  
Vol 24 (6) ◽  
pp. 3211-3227 ◽  
Author(s):  
Paolo Nasta ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Nunzio Romano

Abstract. Although water balance components at the catchment scale are strongly related to annual rainfall, the availability of water resources in Mediterranean catchments also depends on rainfall seasonality. Observed seasonal anomalies in historical records are fairly episodic, but an increase in their frequency might exacerbate water deficit or water excess if the rainy season shortens or extends its duration, e.g., due to climate change. This study evaluates the sensitivity of water yield, evapotranspiration, and groundwater recharge to changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model applied to the upper Alento River catchment (UARC) in southern Italy, where a long time series of daily rainfall is available from 1920 to 2018. We compare two distinct approaches: (i) a “static” approach, where three seasonal features (namely rainy, dry, and transition fixed-duration 4-month seasons) are identified through the standardized precipitation index (SPI) and (ii) a “dynamic” approach based on a stochastic framework, where the duration of two seasons (rainy and dry seasons) varies from year to year according to a probability distribution. Seasonal anomalies occur when the transition season is replaced by the rainy or dry season in the first approach and when season duration occurs in the tails of its normal distribution in the second approach. Results are presented within a probabilistic framework. We also show that the Budyko curve is sensitive to the rainfall seasonality regime in UARC by questioning the implicit assumption of a temporal steady state between annual average dryness and the evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we were able to identify season-dependent regression equations linking water yield to the dryness index in the rainy season.


2020 ◽  
Author(s):  
Nunzio Romano ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Paolo Nasta

<p>Water balance components depend on annual rainfall amount and seasonality in Mediterranean catchments. A high percentage of the annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two approaches: a “static” approach based on the Standardized Precipitation Index (SPI), and a “dynamic” approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The “dynamic” approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.</p>


2021 ◽  
Vol 11 (24) ◽  
pp. 11791
Author(s):  
Megersa Kebede Leta ◽  
Tamene Adugna Demissie ◽  
Muhammad Waseem

Hydrological modeling is a technique for understanding hydrologic characteristics and estimation of the water balance of watersheds for integrated water resources development and management. The Soil and Water Assessment Tool (SWAT) model was used for modeling the hydrological behavior of the Nashe watershed in the north-western part of Ethiopia. The spatial data, daily climate, and stream flow were the required input data for the model. The observed monthly stream flow data at the outlet and selected sub-watersheds in the catchment were used to calibrate and validate the model. The model performance was assessed between the simulated and observed streamflow by using sequential uncertainty fitting-2 (SUFI-2), generalized likelihood uncertainty estimation, parameter solution (Parasol) and particle swarm optimization. The sensitivity of 18 parameters was tested, and the most sensitive parameters were identified. The model performance was evaluated using p and r- factor, coefficient of determination, Nash Sutcliffe coefficient efficiency, percent bias during uncertainty analysis, calibration and validation. Therefore, based on the set of proposed evaluation criteria, the SUFI-2 algorithm has been able to provide slightly more reasonable outcomes and Parasol is the worst compared to the other algorithms. An analysis of monthly and seasonal water balance has been also accomplished for the Nashe catchment. The water balance parameters were distinct for the three seasonal periods in the catchment. The seasonal water budget analysis reveals that the watershed receives around 19%, 69%, and 12% of rainfall through the short rain, long rain and dry seasons, respectively. The received precipitation was lost due to evapotranspiration by 29%, 34% and 37% for each season respectively. The surface runoff contributes to the catchment by 5%, 86% and 9% of the water yield.


Earth ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 225-247
Author(s):  
Mateso Said ◽  
Canute Hyandye ◽  
Ibrahimu Chikira Mjemah ◽  
Hans Charles Komakech ◽  
Linus Kasian Munishi

This study provides a detailed assessment of land cover (LC) changes on the water balance components on data constrained Kikafu-Weruweru-Karanga (KWK) watershed, using the integrated approaches of hydrologic modeling and partial least squares regression (PLSR). The soil and water assessment tool (SWAT) model was validated and used to simulate hydrologic responses of water balance components response to changes in LC in spatial and temporal scale. PLSR was further used to assess the influence of individual LC classes on hydrologic components. PLSR results revealed that expansion in cultivation land and built-up area are the main attributes in the changes in water yield, surface runoff, evapotranspiration (ET), and groundwater flow. The study findings suggest that improving the vegetation cover on the hillside and abandoned land area could help to reduce the direct surface runoff in the KWK watershed, thus, reducing flooding recurring in the area, and that with the ongoing expansion in agricultural land and built-up areas, there will be profound negative impacts in the water balance of the watershed in the near future (2030). This study provides a forecast of the future hydrological parameters in the study area based on changes in land cover if the current land cover changes go unattended. This study provides useful information for the advancement of our policies and practices essential for sustainable water management planning.


2019 ◽  
Author(s):  
Paolo Nasta ◽  
Carolina Allocca ◽  
Roberto Deidda ◽  
Nunzio Romano

Abstract. Water balance components at catchment scale are strongly related to annual rainfall amount. Nonetheless, water resources availability in Mediterranean catchments depends also on rainfall seasonality. Indeed, a high percentage of annual rainfall occurs between late fall and early spring and feeds natural and artificial water reservoirs. This amount of water stored in the mild-rainy season is used to offset rainfall shortages in the hot-dry season (between late spring and early fall). Observed seasonal anomalies in historical records are quite episodic, but an increase of their frequency might exacerbate water stress or water excess if the rainy season shortens or extends its duration, e.g. due to climate change. Hydrological models are useful tools to assess the impact of seasonal anomalies on the water balance components and this study evaluates the sensitivity of water yield, evapotranspiration and groundwater recharge on changes in rainfall seasonality by using the Soil Water Assessment Tool (SWAT) model. The study area is the Upper Alento River Catchment (UARC) in southern Italy where a long time-series of daily rainfall is available from 1920 to 2018. To assess seasonality anomalies, we compare two distinct approaches: a static approach based on the Standardized Precipitation Index (SPI), and a dynamic approach that identifies the rainy season by considering rainfall magnitude, timing, and duration. The former approach rigidly selects three seasonal features, namely rainy, dry, and transition seasons, the latter being occasionally characterized by similar properties to the rainy or dry periods. The dynamic approach, instead, is based on a time-variant duration of the rainy season and enables to corroborate the aforementioned results within a probabilistic framework. A dry seasonal anomaly is characterized by a decrease of 241 mm in annual average rainfall inducing a concurrent decrease of 116 mm in annual average water yield, 60 mm in actual evapotranspiration and 66 mm in groundwater recharge. We show that the Budyko curve is sensitive to the seasonality regime in UARC by questioning the implicit assumption of temporal steady-state between annual average dryness and evaporative index. Although the duration of the rainy season does not exert a major control on water balance, we have been able to identify seasonal-dependent regression equations linking water yield to dryness index over the rainy season.


Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1433
Author(s):  
Navneet Kumar ◽  
Asia Khamzina ◽  
Patrick Knöfel ◽  
John P. A. Lamers ◽  
Bernhard Tischbein

Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land’s productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62% and 100% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km2) in the study region with an average water availability would save 1037 mln m3 of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m3. These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.


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