Decreasing trend of sediment transfer function of the Upper Yellow River, China, in response to human activity and climate change

Figures & data

Fig. 1 (a) Location of study area showing Jingyuan and Quanyanshan stations. (b) Schematic relationship between sediment input and output. Q_s,L, Q_s,T, Q_s,Z, Q_s,Q, Q_s.K and Q_s,KD are annual suspended sediment load (SSL) at Lanzhou, Toudaoguai, Jingyuan (on Zulihe River), Quanyanshan (on Qingshuihe River) and from Kushuihe and 10 kondui, respectively. The sediment division (Q_s,div) with irrigation water is not shown.

Fig. 2 Temporal variation in F_s: (a) variation in F_s and (b) variations in UF_k and UB_k of F_s. Confidence interval between −0.05 < α < 0.05.

Fig. 3 Temporal variation in influencing variables at (a) and (b) basin and (c) channel-reach levels.

Fig. 4 Plots of F_s against annual precipitation (P_L) and air temperature (T_L) for the drainage area above Lanzhou.

Fig. 5 Plots of F_s against variables of human activity. (a) F_s versus R_ra; (b) F_s versus R_div; and (c) F_s versus C_nr.

Table 1 Correlation matrix between F_s and a number of drainage basin influencing variables, all converted to logarithmic values. The last row shows the rank of the correlation coefficients of lnF_s with each influencing variable.

	lnPL	lnTL	lnRre	lnCr,n	lnRdiv	lnFs
lnPL	1.00	0.09	−0.06	0.04	−0.13	0.14
lnTL	0.09	1.00	0.59	−0.71	0.70	−0.70
lnRre	−0.06	0.59	1.00	−0.55	0.70	−0.77
lnCr,n	0.04	−0.71	−0.55	1.00	−0.67	0.78
lnRdiv	−0.13	0.70	0.70	−0.67	1.00	−0.82
lnFs	0.14	−0.70	−0.77	0.78	−0.82	1.00
Rank	5	4	3	2	1

Table 2 Correlation matrix between F_s and a number of influencing variables at channel level, all converted to logarithmic values. The last row shows the rank of the correlation coefficients of lnF_s with each influencing variable.

	lnCmean,H	lnξH	lnQwh	lnRrh	lnCvr	lnQw,div	lnFs
lnCmean,H	1.00	0.90	−0.35	−0.36	−0.32	−0.01	−0.51
lnξH	0.90	1.00	−0.72	−0.69	−0.63	0.12	−0.79
lnQwh	−0.35	−0.72	1.00	0.93	0.86	−0.26	0.89
lnRrh	−0.36	−0.69	0.93	1.00	0.93	−0.17	0.82
lnCv,r	−0.32	−0.63	0.86	0.93	1.00	−0.20	0.80
lnRdiv	0.17	0.52	−0.84	−0.67	−0.65	0.69	−0.84
lnQw,div	−0.01	0.12	−0.26	−0.17	−0.20	1.00	−0.43
lnFs	−0.51	−0.79	0.89	0.82	0.80	−0.43	1.00
Rank	5	4	1	2	3	6

Fig. 6 Plots of F_s against flow variables. (a) F_s versus Q_w,H; (b) F_s versus R_hr; and (c) F_s versus C_vr.

Fig. 7 Plots of F_s against (a) ξ_H and (b) C_mean.

Table 3 Influence of drainage basin variables on the trend of F_s.

	lnPL	lnTL	lnRre	lnCr,n	lnRdiv	lnFs
Correlation coefficient with time	0.10	0.73	0.88	−0.55	0.66	−0.70
Trending with time	Not significant	Increasing	Increasing	Decreasing	Increasing	Decreasing
Correlation coefficient with Fs	0.14	−0.70	−0.77	0.78	−0.82
Direction in which Fs is influenced by each variable	No influence	Make Fs decrease	Make Fs decrease	Make Fs decrease	Make Fs decrease

Table 4 Influence of flow and sediment variables on the trend of F_s.

	lnCmean,H	lnξ	lnQwh	lnRrh	lnCv,r	lnQw,div	lnFs
Correlation coefficient with time	0.24	0.48	−0.66	−0.73	−0.73	0.40	−0.75
Trending with time	Increasing	Increasing	Decreasing	Decreasing	Decreasing	Increasing	Decreasing
Correlation coefficient with Fs	−0.51	−0.79	0.89	0.82	0.80	−0.43
Direction in which Fs is influenced by each variable	Make Fs decrease	Make Fs decrease	Make Fs decrease	Make Fs decrease	Make Fs decrease	Make Fs decrease

Fig. 8 Temporal variations in ξ_H and F_s: (a) scatter plots, and (b) curves fitted by quartic parabolic regression equations.