Modeling hydrological consequences of 21st-Century climate and land use/land cover changes in a mid-high latitude watershed

Abstract

The Naoli River Basin (NRB), a pivotal agricultural production area in China, is poised to undergo substantial impacts on water resources due to projected climate and land use/cover (LULC) changes. Despite its significance in the context of China's expanding farmland construction in the NRB, there exists limited research on the potential repercussions of future shifts in runoff, soil water content (SWC), and evapotranspiration (ET) on crop productivity and water availability (both in terms of quantity and timing). This study employs future LULC maps and an ensemble of ten CMIP6 Global Climate Models (GCMs) across three scenarios to drive the well-calibrated distributed hydrological model, ESSI-3. The objective of present study is aimed on projecting hydrological consequences under climate and land use/land cover changes in near-term (2026–2050), middle-term (2051–2075), and far-term (2076–2100) future in comparison to the baseline period of 1990–2014. Results consistently indicate an increase trend in annual average ET, runoff, and SWC in the NRB across all three future periods under the three SSP scenarios. LULC changes emerge as the primary driver influencing regional hydrological processes in the near future. Notably, under high-emission scenarios, monthly runoff and SWC are projected to significantly increase in March but decrease in April during the middle and far future periods compared to the baseline. This shift is attributed to the anticipated warming of winter and spring, leading to a transition in peak snowmelt from April to March. Concurrently, the expansion of cropland intensifies crop evapotranspiration demand, potentially exacerbating water stress during the early stages of crop growth in April. The findings underscore the importance of addressing the substantial impacts of climate change and land use planning on regional water cycling processes. Early planning to mitigate water shortages during the initial stage of future crop growth is crucial for ensuring food security and managing water-related challenges in the NRB and neighboring mid-high latitude regions.

Keywords

Climate and LULC changes / ESSI-3 / Hydrological modeling / Snowmelt / Naoli River Basin

References

L. Alfieri, P. Burek, L. Feyen, G. Forzieri. Global warming increases the frequency of river floods in Europe. Hydrol. Earth Syst. Sci., 19 (2015), pp. 2247-2260,

A. Aryal, S. Shrestha, M.S. Babel. Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections. Theor. Appl. Climatol., 135 (2019), pp. 193-209,

Y. Bai, J. Zhang, S. Zhang, F. Yao, V. Magliulo. A remote sensing-based two-leaf canopy conductance model: global optimization and applications in modeling gross primary productivity and evapotranspiration of crops. Remote Sens. Environ., 215 (2018), pp. 411-437,

E. Beaulieu, Y. Goddéris, Y. Donnadieu, D. Labat, C. Roelandt. High sensitivity of the continental-weathering carbon dioxide sink to future climate change. Nat. Clim. Chang., 2 (2012), pp. 346-349,

M.L. Berihun, A. Tsunekawa, N. Haregeweyn, D.T. Meshesha, E. Adgo, M. Tsubo, T. Masunaga, A.A. Fenta, D. Sultan, M. Yibeltal, K. Ebabu. Hydrological responses to land use/land cover change and climate variability in contrasting agro-ecological environments of the upper Blue Nile basin. Ethiopia. Sci. Total Environ., 689 (2019), pp. 347-365

T. Chanapathi, S. Thatikonda. Investigating the impact of climate and land-use land cover changes on hydrological predictions over the krishna river basin under present and future scenarios. Sci. Total Environ., 721 (2020), Article 137736

J. Chen, F.P. Brissette, A. Poulin, R. Leconte. Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed. Water Resour. Res., 47 (12) (2011), p. W12509,

H. Chen, W. Zhang, N. Nie, Y. Guo. Long-term groundwater storage variations estimated in the Songhua River Basin by using GRACE products, land surface models, and in-situ observations. Sci. Total Environ., 649 (2019), pp. 372-387,

H. Chen, W. Zhang. Variations of simulated water use efficiency over 2000–2016 and its driving forces in Northeast China. Proc. SPIE., 2019 (2019),

Chong, L. U. O., LIU, H. J., Qiang, F. U., GUAN, H. X., Qiang, Y. E., ZHANG, X. L., KONG, F. C., 2021. Mapping the fallowed area of paddy fields on Sanjiang Plain of Northeast China to assist water security assessments. Journal of Integrative Agriculture19(7):,1885-1896.

Y. Dai, W. Shangguan, Q. Duan, B. Liu, S. Fu, G. Niu. Development of a China dataset of soil hydraulic parameters using pedotransfer functions for land surface modeling. J. Hydrometeorol., 14 (2013), pp. 869-887,

W.T. Dibaba, T.A. Demissie, K. Miegel. Watershed hydrological response to combined land use/land cover and climate change in highland Ethiopia: finchaa catchment. Water, 12 (6) (2020), p. 1801

T.G. Farr, P.A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, M. Paller, E. Rodriguez, L. Roth, D. Seal, S. Shaffer, J. Shimada, J. Umland, M. Werner, M. Oskin, D. Burbank, D. Alsdorf. The shuttle radar topography Mission. Rev. Geophys., 45 (2007),

S. Fatichi, V.Y. Ivanov, A. Paschalis, N. Peleg, P. Molnar, S. Rimkus, J. Kim, P. Burlando, E. Caporali. Uncertainty partition challenges the predictability of vital details of climate change. Earth's Future, 4 (2016), pp. 240-251,

J. Fu, J. Liu, X. Wang, M. Zhang, W. Chen, B. Chen. Ecological risk assessment of wetland vegetation under projected climate scenarios in the sanjiang plain. China. Journal of Environmental Management, 273 (2020), Article 111108,

Golub, M., Thiery, W., Marcé, R., Pierson, D., Vanderkelen, I., Mercado-Bettin, D., Woolway, R., Grant, L., Jennings, E., M. Kraemer, B., Schewe, J., Zhao, F., Frieler, K., Mengel, M., Y. Bogomolov, V., Bouffard, D., Côté, M., Couture, Raoul-Marie., V. Debolskiy, A., Droppers, B., Gal, G., Guo, M., B. G. Janssen, A., Kirillin, G., Ladwig, R., Magee, M., Moore, T., Perroud, M., Piccolroaz, S., Vinnaa, L. R., Schmid, M., Shatwell, T., M. Stepanenko, V., Tan, Z., Woodward, B., Yao, H., Adrian, R., Allan, M., Anneville, O., Arvola, L., Atkins, K., Boegman, L., Carey, C., Christianson, K., Eyto, E., DeGasperi, C., Grechushnikova, M., Hejzlar, J., Joehnk, K., D. Jones, L., Laas, A., B. Mackay, E., Mammarella, L., Markensten, H., McBride, C., Özkundakci, D., Potes, M., Rinke, K., Robertson, D., A. Rusak, J., Salgado, R., Linden, L., Verburg, P., Wain, D., K. Ward, N., Wollrab, S., Zdorovennova, G., 2022. A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector. Geosci. Model Dev., 15, 4597-4623. doi: https://doi.org/10.5194/gmd-15-4597-2022.

J. Gomis-Cebolla, A. Garcia-Arias, M. Perpinyà-Vallès, F. Francés. Evaluation of Sentinel-1, SMAP and SMOS surface soil moisture products for distributed eco-hydrological modelling in Mediterranean forest basins. J. Hydrol., 608 (2022), Article 127569,

L. Gudmundsson, J.B. Bremnes, J.E. Haugen, T. Engen-Skaugen. Downscaling RCM precipitation to the station scale using statistical transformations–a comparison of methods. Hydrol. Earth Syst. Sci., 16 (2012), pp. 3383-3390,

J. He, K. Yang, W. Tang, H. Lu, J. Qin, Y. Chen, X. Li. The first high-resolution meteorological forcing dataset for land process studies over China. Sci. Data, 7 (2020), p. 25,

T. Hengl, J. Mendes de Jesus, G.B. Heuvelink, M. Ruiperez Gonzalez, M. Kilibarda, A. Blagotić, S. Wei, M.N. Wright, X. Geng, B. Bauer-Marschallinger, M.A. Guevara, R. Vargas, R.A. MacMillan, N.H. Batjes, J.G. Leenaars, E. Ribeiro, I. Wheeler, S. Mantel, B. Kempen. SoilGrids250m: global gridded soil information based on machine learning. PLoS One, 12 (2017), p. e0169748

M.R. Herman, A.P. Nejadhashemi, M. Abouali, J.S. Hernandez-Suarez, F. Daneshvar, Z. Zhang, M.C. Anderson, A.M. Sadeghi, C.R. Hain, A. Sharifi. Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability. J. Hydrol., 556 (2018), pp. 39-49,

L.P. Hoang, H. Lauri, M. Kummu, J. Koponen, M.T. Van Vliet, I. Supit, R. Leemans, P. Kabat, F. Ludwig. Mekong River flow and hydrological extremes under climate change. Hydrol. Earth Syst. Sci., 20 (2016), pp. 3027-3041,

R. Knutti, R. Furrer, C. Tebaldi, J. Cermak, G.A. Meehl. Challenges in combining projections from multiple climate models. J. Clim., 23 (2010), pp. 2739-2758,

L. Koot, O.D. Viron, V. Dehant. Atmospheric angular momentum time-series: characterization of their internal noise and creation of a combined series. J. Geod., 79 (2006), pp. 663-674,

E. Kriegler, J. Edmonds, S. Hallegatte, K.L. Ebi, T. Kram, K. Riahi, H. Winkler, D.P. Van Vuuren. A new scenario framework for climate change research: the concept of shared climate policy assumptions. Clim. Change, 122 (2014), pp. 401-414,

Y. Liu, W. Zhang, Z. Zhang. A conceptual data model coupling with physically-based distributed hydrological models based on catchment discretization schemas. J. Hydrol., 530 (2015), pp. 206-215,

D. Long, Y. Pan, J. Zhou, Y. Chen, X. Hou, Y. Hong, B.R. Scanlon, L. Longuevergne. Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models. Remote Sens. Environ., 192 (2017), pp. 198-216,

N. Luo, Y. Guo, J. Chou, Z. Gao. Added value of CMIP6 models over CMIP5 models in simulating the climatological precipitation extremes in China. Int. J. Climatol., 42 (2022), pp. 1148-1164,

R. Ma, C. Cai, J. Wang, T. Wang, Z. Li, T. Xiao, G. Peng. Partial least squares regression for linking aggregate pore characteristics to the detachment of undisturbed soil by simulating concentrated flow in ultisols (subtropical China). J. Hydrol., 524 (2015), pp. 44-52,

B. Martens, D. Miralles, H. Lievens, D. Fernández-Prieto, N.E. Verhoest. Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture. Int. J. Appl. Earth Obs. Geoinf., 48 (2016), pp. 146-162,

B. Martens, D.G. Miralles, H. Lievens, R. Van Der Schalie, R.A. De Jeu, D. Fernández-Prieto, H.E. Beck, W.A. Dorigo, N.E. Verhoest. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev., 10 (2017), pp. 1903-1925,

M. Osuch, D. Lawrence, H.K. Meresa, J.J. Napiorkowski, R.J. Romanowicz. Projected changes in flood indices in selected catchments in Poland in the 21st century. Stoch. Env. Res. Risk A., 31 (2017), pp. 2435-2457,

L. Pagliero, F. Bouraoui, J. Diels, P. Willems, N. McIntyre. Investigating regionalization techniques for large-scale hydrological modelling. J. Hydrol., 570 (2019), pp. 220-235

C. Piani, G.P. Weedon, M. Best, S.M. Gomes, P. Viterbo, S. Hagemann, J.O. Haerter. Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J. Hydrol., 395 (2010), pp. 199-215,

C. Puertes, A. Lidón, C. Echeverria, I. Bautista, M. González-Sanchis, A.D. del Campo, F. Francés. Explaining the hydrological behaviour of facultative phreatophytes using a multi-variable and multi-objective modelling approach. J. Hydrol., 575 (2019), pp. 395-407,

W. Qi, L. Feng, J. Liu, H. Yang. Snow as an important natural reservoir for runoff and soil moisture in Northeast China. J. Geophys. Res. Atmos., 125 (2020),

W. Qi, L. Feng, H. Yang, J. Liu. Warming winter, drying spring and shifting hydrological regimes in Northeast China under climate change. J. Hydrol., 606 (2022), Article 127390,

P. Qi, G. Zhang, Y.J. Xu, Z. Xia, M. Wang. Response of water resources to future climate change in a high-Latitude River basin. Sustainability, 11 (20) (2019), p. 5619,

B. Renard, D. Kavetski, G. Kuczera, M. Thyer, S.W. Franks. Understanding predictive uncertainty in hydrologic modeling: the challenge of identifying input and structural errors. Water Resour. Res., 46 (2010),

Z. Sang, G. Zhang, H. Wang, W. Zhang, Y. Chen, M. Han, K. Yang. Effective solutions to ecological and water environment problems in the sanjiang plain: utilization of farmland drainage resources. Sustainability, 15 (23) (2023), p. 16329

W. Shi, X. Yu, W. Liao, Y. Wang, B. Jia. Spatial and temporal variability of daily precipitation concentration in the Lancang River basin, China. J. Hydrol., 495 (2013), pp. 197-207,

B. Su, J. Huang, X. Zeng, C. Gao, T. Jiang. Impacts of climate change on streamflow in the upper Yangtze River basin. Clim. Change, 141 (2017), pp. 533-546,

Q. Sun, C. Xu, X. Gao, C. Lu, B. Cao, H. Guo, L. Yan, C. Wu, X. He. Response of groundwater to different water resource allocation patterns in the sanjiang plain, Northeast China. J. Hydrol.: Reg. Stud., 42 (2022), Article 101156,

Y. Tian, M.J. Booij, Y.P. Xu. Uncertainty in high and low flows due to model structure and parameter errors. Stoch. Env. Res. Risk A., 28 (2014), pp. 319-332,

D.P. Van Vuuren, J. Edmonds, M. Kainuma, K. Riahi, A. Thomson, K. Hibbard, G.C. Hurtt, T. Kram, V. Krey, J.-F. Lamarque, T. Masui, M. Meinshausen, N. Nakicenovic, S.J. Smith, S.K. Rose. The representative concentration pathways: an overview. Clim. Change, 109 (2011), p. 5,

T. Vetter, S.H. Huang, V. Aich, T. Yang, X. Wang, V. Krysanova, F. Hattermann. Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents. Earth Syst. Dynam., 6 (2015), pp. 17-43,

T. Vetter, J. Reinhardt, M. Flörke, A. Van Griensven, F. Hattermann, S. Huang, H. Koch, I.G. Pechlivanidis, S. Plötner, O. Seidou, B. Su, R.W. Vervoort, V. Krysanova. Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins. Clim. Change, 141 (2017), pp. 419-433,

S. Wang, C. Xu, W. Zhang, H. Chen, B. Zhang. Human-induced water loss from closed inland lakes: hydrological simulations in China’s daihai lake. J. Hydrol., 607 (2022), Article 127552,

S. Wen, B. Su, Y. Wang, J. Zhai, H. Sun, Z. Chen, J. Huang, A. Wang, T. Jiang. Comprehensive evaluation of hydrological models for climate change impact assessment in the upper Yangtze River basin, China. Clim. Change, 163 (2020), pp. 1207-1226,

C. Wu, B.X. Hu, G. Huang, P. Wang, K. Xu. Responses of runoff to historical and future climate variability over China. Hydrol. Earth Syst. Sci., 22 (2018), pp. 1971-1991,

X. Wu, L. Marshall, A. Sharma. Quantifying input error in hydrologic modeling using the bayesian error analysis with reordering (BEAR) approach. J. Hydrol., 598 (2021), Article 126202,

C. Xu, W. Zhang, S. Wang, H. Chen, A. Azzam, B. Zhang, Y. Xu, N. Nie. Spatiotemporal green water dynamics and their responses to variations of climatic and underlying surface factors: a case study in the sanjiang plain, China. J. Hydrol: Regional Studies, 45 (2023), Article 101303,

B. Yan, N.F. Fang, P.C. Zhang, Z.H. Shi. Impacts of land use change on watershed streamflow and sediment yield: an assessment using hydrologic modelling and partial least squares regression. J. Hydrol., 484 (2013), pp. 26-37,

K. Yang, J. He, W. Tang, J. Qin, C.C. Cheng. On downward shortwave and longwave radiations over high altitude regions: observation and modeling in the tibetan plateau. Agric. For. Meteorol., 150 (2010), pp. 38-46,

S. Yang, J. Zhang, S. Zhang, J. Wang, Y. Bai, F. Yao, H. Guo. The potential of remote sensing-based models on global water-use efficiency estimation: an evaluation and intercomparison of an ecosystem model (BESS) and algorithm (MODIS) using site level and upscaled eddy covariance data. Agric. For. Meteorol., 287 (2020), Article 107959

X. Yun, Q. Tang, J. Li, H. Lu, L. Zhang, D. Chen. Can reservoir regulation mitigate future climate change induced hydrological extremes in the lancang-Mekong River basin?. Sci. Total Environ., 785 (2021), Article 147322,

G. Zhang, X. Su, V.P. Singh, O.O. Ayantobo. Appraising standardized moisture anomaly index (SZI) in drought projection across China under CMIP6 forcing scenarios. J. Hydrol.: Reg. Stud., 37 (2021), Article 100898,

T. Zhang, X. Su, G. Zhang, H. Wu, Y. Liu. Projections of the characteristics and probability of spatially concurrent hydrological drought in a cascade reservoirs area under CMIP6. J. Hydrol., 613 (2022), Article 128472,

D. Zhang, W. Zhang. Distributed hydrological modeling study with the dynamic water yielding mechanism and RS/GIS techniques. Proc. SPIE., 2006 (2006),

S. Zhou, W. Zhang, S. Wang, B. Zhang, Q. Xu. Spatial-temporal vegetation dynamics and their relationships with climatic, anthropogenic, and hydrological factors in the Amur River basin. Remote Sens. (Basel), 13 (2021),

H. Zhu, Z. Jiang, J. Li, W. Li, C. Sun, L. Li. Does CMIP6 inspire more confidence in simulating climate extremes over China?. Adv. Atmos. Sci., 37 (2020), pp. 1119-1132,

H. Zhu, Z. Jiang, L. Li. Projection of climate extremes in China, an incremental exercise from CMIP5 to CMIP6. Sci. Bull., 66 (2021), pp. 2528-2537,