Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey

Uysal, Gökçen

doi:10.3390/w14172758

Cited by 7 publications

(2 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. [20][21][22]. The MLP model is a feedforward network with linked neurons systematized into three layers: an input layer, a hidden layer, and an output layer [23].…”

Section: Methods and Datamentioning

confidence: 99%

Assessment of climate change effects on dam reservoir management

Uysal¹,

Doğan²

2022

JCEMI

Self Cite

View full text Add to dashboard Cite

Climate change will alter the inflows into the dam in the future; thus, the balance between water supply and water availability will directly impact the water levels and indirectly affects dam safety. Therefore, estimating the future inflows and reservoir water content can help the operators. In this study, a machine learning Wavelet-MultiLayer Perceptron (W-MLP) method is applied to estimate monthly future projections (2016-2100) of the inflows into the reservoir. The methodology is tested for one of the main water supply reservoirs in Ankara, which distributes annual 142 hm 3 water. The EURO-CORDEX database is used to obtain Regional Climate Model (RCM) simulations of RCA4 (12.5 km) from two different Global Circulation Models (GCMs), MPI-ESM-LR and IPSL-CM5A-MR, under two Representative Concentration Pathways (RCPs) (RCP 4.5 and RCP 8.5) scenarios. The monthly W-MLP models are independently trained and tested for each data set (observed data and GCM outputs). The GCM scenario results indicate a shift in monthly hydrographs for both RCPs projections with a reduction in inflows which will directly change the operation of the reservoir. The daily HEC-ResSim model mimics future water content and releases. According to the results, the annual reduction expected in the future inflows scenarios varies between -3 % to -13% under the RCPs, and the effects on annual reservoir water content are much higher (between -21 % and -37 %). These findings can be used in different risk assessment metrics (reliability, resilience, and vulnerability) to estimate the future effects of dam safety.

show abstract

“…1. [20][21][22]. The MLP model is a feedforward network with linked neurons systematized into three layers: an input layer, a hidden layer, and an output layer [23].…”

Section: Methods and Datamentioning

confidence: 99%

Assessment of climate change effects on dam reservoir management

Uysal¹,

Doğan²

2022

JCEMI

Self Cite

View full text Add to dashboard Cite

show abstract

“…PDIR-NOW has better diurnal cycle representation, rain/no rain days estimation, and regional precipitation patterns compared to the other PERSIANN family products (Nguyen et al, 2020). The inter-annual, annual, and seasonal precipitations are less biased with PDIR-NOW (Huang et al, 2021;Uysal, 2022). In the following, PDIR-NOW will be referred to as PDIR.…”

Section: Pdir-nowmentioning

confidence: 99%

Spatial variability of seasonal precipitation lapse rates in complex topographical regions – application in France

Dura,

Evin,

Favre

et al. 2024

Preprint

View full text Add to dashboard Cite

Abstract. Seasonal precipitation estimation in ungauged mountainous areas is essential for understanding and modeling a physical variable of interest in many environmental applications (hydrology, ecology, cryospheric studies). Precipitation Lapse Rates (PLRs), defined as the increasing or decreasing rate of precipitation amounts with the elevation, play a decisive role in high-altitude precipitation estimation. However, the documentation of PLR in mountainous regions remains weak even though their utilization in environmental applications is frequent. This article intends to assess the spatial variability and the spatial-scale dependence of seasonal PLRs in a varied and complex topography region. At the regional scale (10,000 km2), seven different precipitation products are compared in their ability to reproduce the altitude dependence of the annual/seasonal precipitations of 1,836 stations located in France. The Convection-Permitting Regional Climate Model (CP-RCM) AROME is the best in this regard, despite severe precipitation overestimation in high altitudes. The fine resolution of AROME allows for a precise assessment of the influence of altitude on winter and summer precipitations on 23 massifs at the sub-regional scale (∼ 1,000 km2) and 2,748 small catchments (∼ 100 km2) through linear regressions. With AROME, PLRs are mostly higher in winter at the catchment scale. The variability of PLR is higher in high-altitude regions such as the French Alps, with higher PLRs at the border than inside the massifs. This study emphasizes the interest of conducting PLR investigation at a fine scale to reduce spatial heterogeneity in the seasonal precipitations–altitude relationships.

show abstract

Evaluating the relation between meteorological drought and hydrological drought, and the precipitation distribution for drought classes and return periods over the upper Tigris River catchment

Ozkaya

2023

Theor Appl Climatol

View full text Add to dashboard Cite

Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey

Cited by 7 publications

References 57 publications

Assessment of climate change effects on dam reservoir management

Assessment of climate change effects on dam reservoir management

Spatial variability of seasonal precipitation lapse rates in complex topographical regions – application in France

Evaluating the relation between meteorological drought and hydrological drought, and the precipitation distribution for drought classes and return periods over the upper Tigris River catchment

Contact Info

Product

Resources

About