Gridded data for a hydrological model in a scarce-data basin

Muñoz, Enrique; Arumí, José Luis; Rivera, Diego; Montecinos, Aldo; Billib, Max; Álvarez, César

doi:10.1680/wama.12.00086

Cited by 6 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the cordillera and precordillera in south-central Chile, it is necessary to carry out this correction due to the absence of meteorological stations in the high zones of the Andes, due to which the increase in orographic precipitation is not well measured by the available instruments [25]. Similar analyses have been carried out by Muñoz et al [30,38,39], and Zúñiga et al [40]. Figure 3(a) shows that parameter exhibits greater identifiability during high-flow periods (darker shaded areas and narrower ranges in high-flow periods).…”

Section: Hydrological Processes Representationmentioning

confidence: 86%

Comparison of Stationary and Dynamic Conceptual Models in a Mountainous and Data-Sparse Catchment in the South-Central Chilean Andes

Toledo

Muñoz

Zambrano‐Bigiarini

2015

Advances in Meteorology

Self Cite

View full text Add to dashboard Cite

In recent years, it has been documented that climatic variability influences hydrological processes; however, these influences, such as hydrologic dynamics, have not yet been incorporated into models, which have been assumed as stationary with regard to climatic conditions. In this study, the temporal variability of hydrological processes and their influence on the water balance of a mountainous and data-sparse catchment in Chile are observed and modeled through the comparison of a stationary (time-invariant parameters) and dynamic (time-variant parameters) model. Since conceptual models are the most adequate option for a data-scarce basin, a conceptual model integrated with the Monte Carlo Analysis Toolbox is used to perform the analyses. Simple analyses aimed at increasing the amount of information obtained from models were used. The General and Dynamic Identifiability Analyses were used to perform stationary and dynamic calibration strategies, respectively. As a result we concluded that the dynamic model is more robust than the stationary one. Additionally, DYNIA helped us to observe the temporal variability of hydrological processes. This analysis contributed to a better understanding of hydrological processes in a data-sparse Andean catchment and thus could potentially help reduce uncertainties in the outputs of hydrological models under scenarios of climate change and/or variability. hydrological modeling comes into play, since it is one of the most used tools for water resources management and planning [2].Currently, there are many tools to support water resources planning and management. In particular, conceptual hydrological models have been widely used by the hydrological community [3,4] to provide a better understanding of hydrological processes [5], to estimate long-term water availability [6], and to make projections of climate [7][8][9] and land use change [10,11], among other uses. However, there is still a need not only to reproduce the past behavior of a basin, but also to evaluate the representativeness of the chosen model and its processes to assess the quality of the simulations for a given basin. This must be done not

show abstract

Section: Hydrological Processes Representationmentioning

confidence: 86%

Comparison of Stationary and Dynamic Conceptual Models in a Mountainous and Data-Sparse Catchment in the South-Central Chilean Andes

Toledo

Muñoz

Zambrano‐Bigiarini

2015

Advances in Meteorology

Self Cite

View full text Add to dashboard Cite

show abstract

“…One of the most common ways of determining quality is to assess the accuracy of the data source and test its performance in a hydrologic model, or uncertainty assessments of the potential impacts of weather inputs for model prediction using latent variables [11], simultaneous data assimilation and parameter estimation [12] and using probabilistic techniques such as Bayesian Model Averaging (BMA) or the Integrated Bayesian Uncertainty Estimator (IBUNE) [13,14]. Most studies have focused on evaluating the performance of grid-based precipitation data in simulating hydrologic processes [15][16][17][18][19][20][21][22][23][24][25], while others have focused on evaluating the performances of different parameters in one data set in simulating hydrologic processes [26][27][28][29]. Some studies have evaluated the respective performances of different variables associated with multisource grid-based data in hydrologic modeling [30,31].…”

Section: Introductionmentioning

confidence: 99%

“…However, most of these studies have used data sets on monthly time scales [9,33,35,36], used daily time steps without correction for short-term simulations [8,16,20,22,37,40,41] or evaluated the performances of different variables associated with multisource gridded data in hydrologic modeling [23,24]. In addition, previous studies focused on evaluation of the precipitation data and neglect the temperature data evaluation.…”

Section: Introductionmentioning

confidence: 99%

Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River

Sidike

Chen

et al. 2016

Water

View full text Add to dashboard Cite

Abstract:The main objective of this study is to investigate alternative climate data sources for long-term hydrological modeling. To accomplish this goal, one weather station data set (WSD) and three grid-based data sets including three types of precipitation data and two types of temperature data were selected according to their spatial and temporal details. An accuracy assessment of the grid-based data sets was performed using WSD. Then, the performances of corrected data combination and non-corrected grid-based precipitation and temperature data combinations from multiple sources on simulating river flow in the upstream portion of the Amu Darya River Basin (ADRB) were analyzed using a Soil and Water Assessment Tool (SWAT) model. The results of the accuracy assessments indicated that all the grid-based data sets underestimated precipitation. The Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) precipitation data provided the highest accuracy (correlation coefficients (CF) > 0.89, root mean square error (RMSE) < 41.6 mm), followed by the CRUNCEP reanalysis data (a combination of the CRU TS.3.2 data and the National Centers for Environmental Prediction (NCEP) reanalysis data) (CF > 0.5, RMSE < 58.1 mm) and Princeton's Global Meteorological Forcing Dataset (PGMFD) precipitation data (CF > 0.46, RMSE < 62.8 mm). The PGMFD temperature data exhibited a higher accuracy (CF > 0.98, RMSE < 7.1 • C) than the CRUNCEP temperature data (CF > 0.97, RMSE < 4.9 • C). In terms of the simulation performance, the corrected APHRODITE precipitation and PGMFD temperature data provided the best performance. The CF and Nash-Sutcliffe (NSE) coefficients in the calibration and validation periods were 0.96 and 0.92 and 0.93 and 0.83, respectively. In addition, the combinations of PGMFD temperature data and APHRODITE, PGMFD and CRUNCEP precipitation data produced good results, with NSE ≥ 0.70 and CF ≥ 0.89. The combination of CRUNCEP temperature data and APHRODITE precipitation produced a satisfactory result, with NSE = 0.58 and CF = 0.82. The combinations of CRUNCEP temperature data and PGMFD and CRUNCEP precipitation data produced poor results.

show abstract

“…To perform the modeling, precipitation and temperature data were obtained from the 0.5 • -resolution Global Gridded Dataset published by Willmot and Matsuura [61]. This dataset was validated for the study area in Muñoz et al [62]. To estimate PET, the Thornthwaite method [63] was used.…”

Section: Modeling Approach and Datamentioning

confidence: 99%

An Adaptive Basin Management Rule to Improve Water Allocation Resilience under Climate Variability and Change—A Case Study in the Laja Lake Basin in Southern Chile

Muñoz

Guzmán

Medina

et al. 2019

Water

Self Cite

View full text Add to dashboard Cite

Due to population growth and expansion in the agricultural and industrial sectors, the demand for water has increased. However, water availability in some regions has decreased due to climate change trends and variability, necessitating innovative strategies and adaptation in water allocation to avoid conflicts among users in a hydrological system. This paper presents a resilience analysis and a conceptual hydrological modeling approach to evaluate the resilience capacity of a new water allocation rule in the Laja Lake basin in southern Chile. Resilience assessments included absorptive and adaptive capacities with four system states: resilient, susceptible, resistant, and vulnerable. A modeling approach was used considering the climate variability uncertainty and climate change trends of the Laja system. Characterization of adaptive and absorptive capacities showed that the Laja Lake basin moved from resistant to vulnerable. Hydrological modeling analyses showed that after a new water allocation agreement, the Laja Lake system is moving from vulnerable to susceptible, since the new rule has more adaptive alternatives to face climate variability. The new rule diminishes the possibilities of conflicts among users, ensuring the fulfillment of water needs for uses such as farming and ecosystem services such as landscaping, and allows for increased water allocation for energy in wet hydrological years.

show abstract

Gridded data for a hydrological model in a scarce-data basin

Cited by 6 publications

References 35 publications

Comparison of Stationary and Dynamic Conceptual Models in a Mountainous and Data-Sparse Catchment in the South-Central Chilean Andes

Comparison of Stationary and Dynamic Conceptual Models in a Mountainous and Data-Sparse Catchment in the South-Central Chilean Andes

Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River

An Adaptive Basin Management Rule to Improve Water Allocation Resilience under Climate Variability and Change—A Case Study in the Laja Lake Basin in Southern Chile

Contact Info

Product

Resources

About