Surface water resources assessment in scarcely gauged basins in the north of Spain

Garcı́a, Andrés; Sáinz, Ángel Gutiérrez; Revilla, José A.; Álvarez, César; Juanes, José A.; Puente, Araceli

doi:10.1016/j.jhydrol.2008.04.019

Cited by 79 publications

(53 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The values of E and R 2 were improved to 0.63-0.88. These results are quite satisfactory and complement well some previous studies such as Meenu et al [22] in India, Verma et al [23] in India, Yimer et al [24] in Ethiopia, and Garcia et al [25] in Spain. All these studies also used HEC-HMS to simulate streamflow for climate change studies, with E ranging from 0.48-0.83 and R 2 from 0.63-0.84.…”

Section: Projected Changes In Streamflowsupporting

confidence: 91%

“…The calibration of a model is a process in which the model's parameters are adjusted in such a way that the simulated flow captures the variations of the observed flow [25]. In this study, a split sample method was used for calibration and validation.…”

Section: The Model's Calibration and Validationmentioning

confidence: 99%

“…It is the second largest reservoir of Pakistan. Although HEC-HMS, a well-known hydrological model, has been successfully used for small to large and plains to mountainous areas of the world [22][23][24][25][26][27], almost no studies have been reported in Pakistan that use HEC-HMS for the assessment of climate change impacts on water resources.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Potential Impacts of Climate Change on Water Resources in the Kunhar River Basin, Pakistan

Mahmood

Jia

Babel

2016

Water

View full text Add to dashboard Cite

Abstract:Pakistan is one of the most highly water-stressed countries in the world and its water resources are greatly vulnerable to changing climatic conditions. The present study investigates the possible impacts of climate change on the water resources of the Kunhar River basin, Pakistan, under A2 and B2 scenarios of HadCM3, a global climate model. After successful development of the hydrological modeling system (HEC-HMS) for the basin, streamflow was simulated for three future periods (2011-2040, 2041-2070, and 2071-2099) and compared with the baseline period to explore the changes in different flow indicators such as mean flow, low flow, median flow, high flow, flow duration curves, temporal shift in peaks, and temporal shifts in center-of-volume dates. From the results obtained, an overall increase in mean annual flow was projected in the basin under both A2 and B2 scenarios. However, while summer and autumn showed a noticeable increase in streamflow, spring and winter showed decreased streamflow. High and median flows were predicted to increase, but low flow was projected to decrease in the future under both scenarios. Flow duration curves showed that the probability of occurrence of flow is likely to be more in the future. It was also noted that peaks were predicted to shift from June to July in the future, and the center-of-volume date-the date at which half of the annual flow passes-will be delayed by about 9-17 days in the basin, under both A2 and B2 scenarios. On the whole, the Kunhar basin will face more floods and droughts in the future due to the projected increase in high flow and decrease in low flow and greater temporal and magnitudinal variations in peak flows. These results highlight how important it is to take cognizance of the impact of climate change on water resources in the basin and to formulate suitable policies for the proper utilization and management of these resources.

show abstract

Section: Projected Changes In Streamflowsupporting

confidence: 91%

Section: The Model's Calibration and Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Potential Impacts of Climate Change on Water Resources in the Kunhar River Basin, Pakistan

Mahmood

Jia

Babel

2016

Water

View full text Add to dashboard Cite

show abstract

“…In the case of rainfall-runoff models, it is necessary to have observed flow data to be able to develop this process (García et al 2008). Due to gauge scarcity of Khosrow Shirin watershed, 7 of the 12 parameters needed for the SMA algorithm [canopy interception storage, surface depression storage, maximum infiltration rate, maximum soil storage, tension zone storage, soil zone infiltration rate, and groundwater 1 (GW1) percolation rate] were estimated by means of model calibration.…”

Section: Resultsmentioning

confidence: 99%

Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting

Rezaeianzadeh

Stein

Tabari

et al. 2013

Int. J. Environ. Sci. Technol.

View full text Add to dashboard Cite

Artificial neural networks (ANNs) are used by hydrologists and engineers to forecast flows at the outlet of a watershed. They are employed in particular where hydrological data are limited. Despite these developments, practitioners still prefer conventional hydrological models. This study applied the standard conceptual HEC-HMS's soil moisture accounting (SMA) algorithm and the multi layer perceptron (MLP) for forecasting daily outflows at the outlet of Khosrow Shirin watershed in Iran. The MLP [optimized with the scaled conjugate gradient] used the logistic and tangent sigmoid activation functions resulting into 12 ANNs. The R 2 and RMSE values for the best trained MPLs using the tangent and logistic sigmoid transfer function were 0.87, 1.875 m 3 s -1 and 0.81, 2.297 m 3 s -1 , respectively. The results showed that MLPs optimized with the tangent sigmoid predicted peak flows and annual flood volumes more accurately than the HEC-HMS model with the SMA algorithm, with R 2 and RMSE values equal to 0.87, 0.84 and 1.875 and 2.1 m 3 s -1 , respectively. Also, an MLP is easier to develop due to using a simple trial and error procedure. Practitioners of hydrologic modeling and flood flow forecasting may consider this study as an example of the capability of the ANN for real world flow forecasting.

show abstract

“…The estimated parameter values are adjusted until the value of the selected objective function--in this case the goodness-of-fit between the observed and computed total runoff volume from the catchment--is minimized (Scharffenberg and Fleming 2010). For this study, initial values for all 23 parameters (listed in Table 1) were obtained from geology, soil and land use maps and from published sources (Rawls et al 1982, USDA 1986, Bennett 1998, McCuen 1998, Singhal and Gupta 1999, Chainuvati and Athipanan 2001, Breuer et al 2003, Fleming and Neary 2004, Garcı´a et al 2008, McEnroe 2010. A standard calibration-validation procedure was then followed (as initially set out in Section 2.1 of Trucano et al 2006), with parameter optimisation taking place within the calibration stage.…”

Section: Catchment Rainfall-runoff Modellingmentioning

confidence: 99%

Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran

Hajian

Dykes

Zahabiyoun

et al. 2016

Hydrological Sciences Journal

View full text Add to dashboard Cite

Abstract:The southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall-runoff model was used with downscaled future rainfall and temperature data from 13 Global Circulation Models, and meteorological and hydrometric data from the Casilian (or 'Kassilian') Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of droughts. "Flash floods" arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards. Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran AbstractThe southern coast of the Caspian Sea in northern Iran is bordered by a mountain range with forested catchments which are susceptible to droughts and floods. This paper examines possible changes to runoff patterns from one of these catchments in response to climate change scenarios. The HEC-HMS rainfall-runoff model was used with downscaled future rainfall and temperature data from 13 Global Circulation Models, and meteorological and hydrometric data from the Casilian (or 'Kassilian') Catchment. Annual and seasonal predictions of runoff change for three future emissions scenarios were obtained, which suggest significantly higher spring rainfall with increased risk of flooding and significantly lower summer rainfall leading to a higher probability of droughts. "Flash floods" arising from extreme rainfall may become more frequent, occurring at any time of year. These findings indicate a need for strategic planning of water resource management and mitigation measures for increasing flood hazards.

show abstract

Surface water resources assessment in scarcely gauged basins in the north of Spain

Cited by 79 publications

References 11 publications

Potential Impacts of Climate Change on Water Resources in the Kunhar River Basin, Pakistan

Potential Impacts of Climate Change on Water Resources in the Kunhar River Basin, Pakistan

Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting

Prediction of climate change effects on the runoff regime of a forested catchment in northern Iran

Contact Info

Product

Resources

About