Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D.K., Knapp, K.R., Cecil, L.D., Nelson, B.R., Prat, O.P., 2015. PERSIANN-CDR: daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bull. America. Meteorol. Soci. 96(1), 69-83.
Dang, T.D., Vu, D.T., Chowdhury, A.F.M.K., Galelli, S., 2020. A software package for the representation and optimization of water reservoir operations in the VIC hydrologic model. Environ. Model. Soft. 126, 104673.
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolu. Comput. 6(2), 182-197.
Dwarakish, G., Ganasri, B., 2015. Impact of land use change on hydrological systems: A review of current modeling approaches. Cogent Geosci. 1(1), 1115691.
Ghoreishi GharahTikan, S., Gharechelou, S., Mahjoobi, E., Golian, S., Salehi, H., 2022. Evaluation of available surface water resources in Qarah Tikan border basin using satellite products and GIS. Water Soil Manage. Model. 2(1), 1-13.
Gupta, H.V., Kling, H., Yilmaz, K.K., Martinez, G.F., 2009. Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. J. Hydrol. 377(1-2), 80-91.
Islam, M.S., Oki, T., Kanae, S., Hanasaki, N., Agata, Y., Yoshimura, K., 2007. A grid-based assessment of global water scarcity including virtual water trading. Water Resou. Manage. 21(1), 19-33.
Kauffeldt, A., Wetterhall, F., Pappenberger, F., Salamon, P., Thielen, J., 2016. Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level. Environ. Model. Soft. 75, 68-76.
Li, Q., Yu, X., Xin, Z., Sun, Y., 2013. Modeling the effects of climate change and human activities on the hydrological processes in a semiarid watershed of loess plateau. J. Hydrol. Engin. 18(4), 401-412.
Liang, J., Liu, Q., Zhang, H., Li, X., Qian, Z., Lei, M., Li, X., Peng, Y., Li, S., Zeng, ., 2020. Interactive effects of climate variability and human activities on blue and green water scarcity in rapidly developing watershed. J. Cleaner Produc. 265, 121834.
Liang, X., Lettenmaier, D.P., Wood, E.F., Burges, S.J., 1994. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophysi. Res.: Atmos. 99(D7), 14415-14428.
Markert, K.N., Griffin, R.E., Limaye, A S., McNider, R.T., 2018. spatial modeling of land cover/land use change and its effects on hydrology within the Lower Mekong Basin. In Land-Atmospheric Research Applications in South and Southeast Asia (pp. 667-698). Springer.
Martin, E., Gascoin, S., Grusson, Y., Murgue, C., Bardeau, M., Anctil, F., Ferrant, S., Lardy, R., Le Moigne, P., Leenhardt, D., 2016. On the use of hydrological models and satellite data to study the water budget of river basins affected by human activities: examples from the Garonne Basin of France. Surv. Geophys. 37, 223-247.
Mauser, W., Bach, H., 2009. PROMET–Large scale distributed hydrological modelling to study the impact of climate change on the water flows of mountain watersheds. J. Hydrol. 376(3-4), 362-377.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., 2021. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth Sys. Sci. Data 13(9), 4349-438.
Nachtergaele, F., Velthuizen, H., Verelst, L., Wiberg, D., 2009. Harmonized World Soil Database (HWSD). Food and Agriculture Organization of the United Nations, Rome.
Nepal, S., Krause, P., Flügel, W.A., Fink, M., Fischer, C., 2014. Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model. Hydrolo. Proces. 28(3), 1329-1344.
Sabzi, H.Z., Moreno, H.A., Fovargue, R., Xue, X., Hong, Y., Neeson, T.M., 2019. Comparison of projected water availability and demand reveals future hotspots of water stress in the Red River basin, USA. J. Hydrol.: Regional Studies 26, 100638.
Salehi, H., Sadeghi, M., Golian, S., Nguyen, P., Murphy, C., Sorooshian, S., 2022. The Application of PERSIANN Family Datasets for Hydrological Modeling. Remote Sens. 14(15), 3675.
Sayama, T., McDonnell, J.J., 2009. A new time‐space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale. Water Resou. Res. 45.
Schulzweida, U., Kornblueh, L., Quast, R., 2006. CDO user’s guide. Climate Data Operators, Version, 1(6), 205-209.
Shayeghi, A., Azizian, A., Brocca, L., 2020. Reliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin, Iran. Hydrol. Sci. J. 65(2), 296-310.
Strahler, A.H., Muller, J., Lucht, W., Schaaf, C., Tsang, T., Gao, F., Li, X., Lewis, P., Barnsley, M.J., 1999. MODIS BRDF/albedo product: algorithm theoretical basis document version 5.0. MODIS documentation, 23(4), 42-47.
Sulla-Menashe, D., Friedl, M.A., 2018. User guide to collection 6 MODIS land cover (MCD12Q1 and MCD12C1) product. USGS: Reston, VA, USA, 1-18.
Wang, W., Shao, Q., Yang, T., Peng, S., Xing, W., Sun, F., Luo, Y., 2013. Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin, China. Hydrolo. Proces. 27(8), 1158-1174.