Artificial Neural Networks in Hydrology. I: Preliminary Concepts. (2000). Journal of Hydrologic Engineering, 5(2), 115–123. https://doi.org/10.1061/(asce)1084-0699(2000)5:2(115)
Bakhtiari, B. (2018). Probable Maximum Precipitation Estimation in a Humid Climate. https://doi.org/10.5194/nhess-2018-38-ac1
Beven, K. (2012). Rainfall-Runoff Modelling. https://doi.org/10.1002/9781119951001
Change, I. P. on C. (2014). Climate Change 2014 Mitigation of Climate Change. https://doi.org/10.1017/cbo9781107415416
Choi, Y. S., Shin, M.-J., & Kim, K. T. (2020). A Study on a Simple Algorithm for Parallel Computation of a Grid-Based One-Dimensional Distributed Rainfall-Runoff Model. KSCE Journal of Civil Engineering, 24(2), 682–690. https://doi.org/10.1007/s12205-020-2458-z
Ciupak, M., Ozga-Zielinski, B., Adamowski, J., Deo, R. C., & Kochanek, K. (2019). Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model. Water, 11(10), 2138. https://doi.org/10.3390/w11102138
Ehteram, M., Binti Othman, F., Mundher Yaseen, Z., Abdulmohsin Afan, H., Falah Allawi, M., Bt. Abdul Malek, M., … El-Shafie, A. (2018). Improving the Muskingum Flood Routing Method Using a Hybrid of Particle Swarm Optimization and Bat Algorithm. Water, 10(6), 807. https://doi.org/10.3390/w10060807
Farzin, S., Singh, V., Karami, H., Farahani, N., Ehteram, M., Kisi, O., … El-Shafie, A. (2018). Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm. Water, 10(9), 1130. https://doi.org/10.3390/w10091130
Ferraro, D., Costabile, P., Costanzo, C., Petaccia, G., & Macchione, F. (2020). A spectral analysis approach for the a priori generation of computational grids in the 2-D hydrodynamic-based runoff simulations at a basin scale. Journal of Hydrology, 582, 124508. https://doi.org/10.1016/j.jhydrol.2019.124508
Gan, F., He, B., & Qin, Z. (2020). Hydrological response and soil detachment rate from dip/anti-dip slopes as a function of rock strata dip in karst valley revealed by rainfall simulations. Journal of Hydrology, 581, 124416. https://doi.org/10.1016/j.jhydrol.2019.124416
Goly, A., & Teegavarapu, R. S. V. (2013). Multi-Objective Optimization Methods for Bias Correction of Statistically Downscaled Precipitation. World Environmental and Water Resources Congress 2013. https://doi.org/10.1061/9780784412947.116
Kimura, N., Kiri, H., Kanada, S., Kitagawa, I., Yoshinaga, I., & Aiki, H. (2019). Flood Simulations in Mid-Latitude Agricultural Land Using Regional Current and Future Extreme Weathers. Water, 11(11), 2421. https://doi.org/10.3390/w11112421
Li, Z., Shi, X., Tang, Q., Zhang, Y., Gao, H., Pan, X., … Zhou, P. (2020). Partitioning the contributions of glacier melt and precipitation to the 1971–2010 runoff increases in a headwater basin of the Tarim River. Journal of Hydrology, 583, 124579. https://doi.org/10.1016/j.jhydrol.2020.124579
Ling, L., Yusop, Z., Yap, W.-S., Tan, W. L., Chow, M. F., & Ling, J. L. (2019). A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China. Water, 12(1), 60. https://doi.org/10.3390/w12010060
Mohamadi, S., Sammen S. S., Panahi, F. et al. Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm. Nat Hazards 104, 537–579 (2020). https://doi.org/10.1007/s11069-020-04180-9
Noji, E. K. (1991). Natural Disasters. Critical Care Clinics, 7(2), 271–292. https://doi.org/10.1016/s0749-0704(18)30306-3
Ohl, C. A., & Tapsell, S. (2000). Flooding and human health. BMJ (Clinical Research Ed.), 321(7270), 1167–1168. https://doi.org/10.1136/bmj.321.7270.1167
Ren, X., Hong, N., Li, L., Kang, J., & Li, J. (2020). Effect of infiltration rate changes in urban soils on stormwater runoff process. Geoderma, 363, 114158. https://doi.org/10.1016/j.geoderma.2019.114158
Rientjes, T. H. M., Muthuwatta, L. P., Bos, M. G., Booij, M. J., & Bhatti, H. A. (2013). Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration. Journal of Hydrology, 505, 276–290. https://doi.org/10.1016/j.jhydrol.2013.10.006
Pham, Q.B., Mohammadpour, R., Linh, N.T.T. et al. Application of soft computing to predict water quality in wetland. Environ Sci Pollut Res 28, 185–200 (2021). https://doi.org/10.1007/s11356-020-10344-8
Sammen S. S.; Ghorbani, M.A.; Malik, A.; Tikhamarine, Y.; AmirRahmani, M.; Al-Ansari, N.; Chau, K.-W. Enhanced Artificial Neural Network with Harris Hawks Optimization for Predicting Scour Depth Downstream of Ski-Jump Spillway. Appl. Sci. 2020, 10, 5160. https://doi.org/10.3390/app10155160
Smith, H. F. (1965). Handbook of Applied Hydrology. A compendium of water-resources technology. Van Te Chow, Ed. McGraw-Hill, New York, 1964. 1418 pp. Illus. $39.50. Science, 148(3667), 219. https://doi.org/10.1126/science.148.3667.219
Song, J.-H., Her, Y., Suh, K., Kang, M.-S., & Kim, H. (2019). Regionalization of a Rainfall-Runoff Model: Limitations and Potentials. Water, 11(11), 2257. https://doi.org/10.3390/w11112257
Tikhamarine, Y., Malik, A., Pandey, K. et al. Monthly evapotranspiration estimation using optimal climatic parameters: efficacy of hybrid support vector regression integrated with whale optimization algorithm. Environ Monit Assess 192, 696 (2020). https://doi.org/10.1007/s10661-020-08659-7
Torabi Haghighi, A., Sadegh, M., Behrooz-Koohenjani, S., Hekmatzadeh, A. A., Karimi, A., & Kløve, B. (2019). The mirage water concept and an index-based approach to quantify causes of hydrological changes in semi-arid regions. Hydrological Sciences Journal, 65(2), 311–324. https://doi.org/10.1080/02626667.2019.1691728
Velázquez-Zapata, J. A. (2019). Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin. Water, 11(10), 2110. https://doi.org/10.3390/w11102110
Vitousek, S., Barnard, P. L., Fletcher, C. H., Frazer, N., Erikson, L., & Storlazzi, C. D. (2017). Doubling of coastal flooding frequency within decades due to sea-level rise. Scientific Reports, 7(1), 1399. https://doi.org/10.1038/s41598-017-01362-7
Yang, X., Magnusson, J., Huang, S., Beldring, S., & Xu, C.-Y. (2020). Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions. Journal of Hydrology, 582, 124357. https://doi.org/10.1016/j.jhydrol.2019.124357