于SWAT模型的渭河流域干旱时空分布

doi:10.18306/dlkxjz.2015.09.008

Abstract

Abstract:

Drought is a complex natural hazard that is difficult to define and assess. By considering the hydrological cycle of river basins, a drought evaluation model SWAT-PDSI was constructed based on the Palmer Drought Severity Index(PDSI) and simulated results of SWAT (Soil and Water Assessment Tool) in the Weihe River Basin. Moreover, characteristics of the spatiotemporal distribution and frequency of drought hazard in the basin were analyzed. Results showed that: (1) The calibrated and validated SWAT model can be used to predict the hydrological process in the Weihe River Basin since it results in similar simulated trend of change as the observed data; (2) The SWAT-PDSI model based on SWAT and PDSI well describes the characteristics of drought in the Weihe River Basin as verified by the drought indices in 1995; (3) Temporally, the Weihe River Basin, Weihe River mainstream, and Jinghe River Basin showed a drying trend and the Beiluohe River Basin showed a wetter trend, but these were not statistically significant at the 0.05 confidence level; (4) Spatially, the annual average of SWAT-PDSI was between -1 and 1 in most subbasins; (5) High frequency drought areas were mainly distributed in the upstream of the Beiluohe River Basin and the Jinghe River Basin.

Key words: SWAT model, PDSI, drought assessment, the Weihe River Basin

Anzhou ZHAO, Xianfeng LIU, Xiufang ZHU, Yaozhong PAN, Yizhan LI. Spatiotemporal patterns of droughts based on SWAT model for the Weihe River Basin[J].PROGRESS IN GEOGRAPHY, 2015, 34(9): 1156-1166.

Figures/Tables 11

Fig.1

Tab.1

Calculation equation of each water budget item"

水文要素	来源及计算公式
PET_i（第i个月的潜在蒸散发）	由SWAT模型直接输出
ET_i（第i个月的实际蒸散发）	由SWAT模型直接输出
SW_i_-1（月初土壤含水量）	由SWAT模型直接输出
SW_i（月初末土壤含水量）	由SWAT模型直接输出
RO_i（实际地表径流）	由SWAT模型直接输出
AWC_i（田间有效持水量）	参考联合国粮农组织(FAO)和维也纳国际应用系统研究所(IIASA)构建的世界和谐土壤属性数据库得到
PR_i（可能补水量）	$P R i = AWC - S W i - 1$
R_i（实际补水量）	$R i = max (0, (S W i - S W i - 1))$
PRO_i（可能径流量）	$PR O i = AWC - P R i = S W i$
L_i（实际失水量）	$L i = max (0, (S W i - 1 - S W i))$
PL_i(可能失水量)	$P L i = min (P E i, S W i - 1)$

Tab.1

Tab.2

Fig.2

Tab.3

Fig.3

Fig.4

Fig.5

Tab.4

Fig.6

Fig.7

References 35

[1]	陈峰, 袁玉江, 魏文寿, 等. 2011. 腾格里沙漠南缘近315年5-6月PDSI指数变化[J]. 地理科学, 31(4): 434-439.
	[Chen F, Yuan Y J, Wei W S, et al. Reconstruction of May-June Palmer Drought Severity Index at south margin of Tengger Desert, China since A.D.1691[J]. Scientia Geographica Sinica, 31(4): 434-439.]
[2]	陈昱潼, 畅建霞, 黄生志, 等. 2014. 基于PDSI的渭河流域干旱变化特征[J]. 自然灾害学报, 23(5): 29-37.
	[Chen Y T, Chang J X, Huang S Z, et al.2014. Variation characteristics of drought in Weihe River Basin based on Palmer Drought Severity Index[J]. Journal of Natural Disasters, 23(5): 29-37.]
[3]	冯夏清, 章光新, 尹雄锐. 2010. 基于SWAT模型的乌裕尔河流域气候变化的水文响应[J]. 地理科学进展, 29(7): 827-832.
	[Feng X Q, Zhang G X, Yi X R.Study on the hydrological response to climate change in Wuyur River Basin based on the SWAT model[J]. Progress in Geography, 29(7): 827-832.]
[4]	韩兰英, 张强, 姚玉璧, 等. 2014. 近60年中国西南地区干旱灾害规律与成因[J]. 地理学报, 69(5): 632-639.
	[Han L Y, Zhang Q, Yao Y B, et al.2014. Characteristics and origins of drought disasters in Southwest China in nearly 60 years[J]. Acta Geographica Sinica, 69(5): 632-639.]
[5]	史晓亮. 2013. 基于SWAT模型的滦河流域分布式水文模拟与干旱评价方法研究[D]. 北京: 中国科学院大学.
	[Shi X L.2013. Study on distributed hydrological simulation and drought evaluation method in Luanhe River Basin based on SWAT model[D]. Beijing, China: University of Chinese Academy of Sciences.]
[6]	徐宗学, 程磊. 2010. 分布式水文模型研究与应用进展[J]. 水利学报, 41(9): 1009-1017.
	[Xu Z X, Chen L.2010. Progress on studies and applications of the distributed hydrological models[J]. Journal of Hydraulic Engineering, 41(9): 1009-1017.]
[7]	许继军, 杨大文. 2010. 基于分布式水文模拟的干旱评估预报模型研究[J]. 水利学报, 41(6): 739-747.
	[Xu J J, Yang D W.2010. New model for drought estimation and prediction based on distributed hydrological simulation[J]. Journal of Hydraulic Engineering, 41(6): 739-747.]
[8]	杨新, 李士高. 1997. 1995年陕西特大干旱[J]. 灾害学, 12(1): 77-79.
	[Yang X, Li S G.1997. The heaviest drought in Shaanxi Province in 1995[J]. Journal of Catastrophology, 12(1): 77-79.]
[9]	余优森, 张平兰, 万信, 等. 1997. 1995年甘肃农业土壤干旱及其对产量的影响[J]. 干旱地区农业研究, 15(3): 27-32.
	[Yu Y S, Zhang P L, Wang X, et al.1997. Farming soil drought and its effect on crop yield in Gansu in 1995[J]. Agricultural Research in the Arid Areas, 15(3): 27-32.]
[10]	张永, 陈发虎, 勾晓华, 等. 2007. 中国西北地区季节间干湿变化的时空分布: 基于PDSI数据[J]. 地理学报, 62(11): 1142-1152.
	[Zhang Y, Chen F H, Gou X H, et al.2007. The temporal and spatial distribution of seasonal dry-wet changes over the Northwestern China: based on PDSI. Acta Geographica Sinica, 62(11): 1142-1152.]
[11]	左德鹏, 徐宗学, 李景玉, 等. 2011. 气候变化情景下渭河流域潜在蒸散量时空变化特征[J]. 水科学进展, 22(4): 455-461.
	[Zuo D P, Xu Z X, Li J Y, et al.2011. Spatiotemporal characteristics of potential evapotranspiration in the Weihe River Basin under future climate change[J]. Advance in Water Science, 22(4): 455-461.]
[12]	Abbaspour K C.2007. User manual for SWAT-CUP, SWAT calibration and uncertainty analysis programs[Z]. Duebendorf, Switzerland: Swiss Federal Institute of Aquatic Science and Technology.
[13]	Agboma C O, Yirdaw S Z, Snelgrove K R.2009. Intercomparison of the total storage deficit index (TSDI) over two Canadian Prairie catchments[J]. Journal of Hydrology, 374(3-4): 351-359.
[14]	Al-Qinna M I, Hammouri N A, Obeidat M M, et al.2011. Drought analysis in Jordan under current and future climates[J]. Climatic Change, 106(3): 421-440.
[15]	Chen S, Li R.2013. Assessment of surface water resources and evapotranspiration in the Haihe River basin of China using SWAT model[J]. Hydrological Processes, 27(8): 1200-1222.
[16]	Dai A G.2011. Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900-2008[J]. Journal of Geophysical Research, 116(D12): D12115, doi: 10.1029/2010JD015541.
[17]	Dai A G, Trenberth K E, Qian T T.2004. A global dataset of Palmer Drought Severity Index for 1870-2002: relationship with soil moisture and effects of surface warming[J]. Journal of Hydrometeorology, 5(6): 1117-1130.
[18]	Freer J, Beven K, Ambroise B.1996. Bayesian estimation of uncertainty in runoff prediction and the value of data: an application of the GLUE approach[J]. Water Resources Research, 32(7): 2161-2173.
[19]	Geza M, Mccray J E.2008. Effects of soil data resolution on SWAT model stream flow and water quality predictions[J]. Journal of Environmental Management, 88(3): 393-406.
[20]	He B, Lü A F, Wu J J, et al.2011. Drought hazard assessment and spatial characteristics analysis in China[J]. Journal of Geographical Sciences, 21(2): 235-249.
[21]	He H M, Zhang Q F, Zhou J, et al.2009. Coupling climate change with hydrological dynamic in Qinling Mountains, China[J]. Climatic Change, 94(3): 409-427.
[22]	Hua L J, Ma Z G, Zhong L H.2011. A comparative analysis of primary and extreme characteristics of dry or wet status between Asia and North America[J]. Advances in Atmospheric Sciences, 28(2): 352-362.
[23]	Krause P, Boyle D P, Bäse F.2005. Comparison of different efficiency criteria for hydrological model assessment[J]. Advances in Geosciences, European Geosciences Union (EGU), 5: 89-97.
[24]	Motovilov Y G, Gottschalk L, Engeland K, et al.1999. Validation of a distributed hydrological model against spatial observations[J]. Agricultural and Forest Meteorology, 98-99: 257-277.
[25]	Naramngam S, Tong S T Y.2013. Environmental and economic implications of various conservative agricultural practices in the Upper Little Miami River Basin[J]. Agricultural Water Management, 119: 65-79.
[26]	Narasimhan B, Srinivasan R.2005. Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring[J]. Agricultural and Forest Meteorology, 133(1-4): 69-88.
[27]	Neitsch S L, Arnold J G, Kiniry J R, et al.2011. Soil and water assessment tool: theoretical documentation version 2009[R]. Texas water resources institute technical report No 365. College Station, TX: Texas A&M University System.
[28]	Palmer W C.1965. Meteorological drought[R]. Washington, DC: US Department of Commerce, Weather Bureau.
[29]	Tesemma Z K, Mohamed Y A, Steenhuis T S.2010. Trends in rainfall and runoff in the Blue Nile Basin: 1964-2003[J]. Hydrological Processes, 24(25): 3747-3758.
[30]	Wang A H, Lettenmaier D P, Sheffield J.2011. Soil moisture drought in China, 1950-2006[J]. Journal of Climate, 24(13): 3257-3271.
[31]	Wu P T, Jin J M, Zhao X N.2010. Impact of climate change and irrigation technology advancement on agricultural water use in China[J]. Climatic Change, 100(3): 797-805.
[32]	Xu Z X, Pang J P, Liu C M, et al.2009. Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model[J]. Hydrological Processes, 23(25): 3619-3630.
[33]	Yan D H, Shi X L, Yang Z Y, et al.2013. Modified palmer drought severity index based on distributed hydrological simulation[J]. Mathematical Problems in Engineering, doi: 10.1155/2013/327374.
[34]	Zhang B Q, Wu P T, Zhao X N, et al.2013. A drought hazard assessment index based on the VIC-PDSI model and its application on the Loess Plateau, China[J]. Theoretical and Applied Climatology, 114(1): 125-138.
[35]	Zhao M S, Running S W.2010. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009[J]. Science, 329: 940-943.

指数值(x)	等级划分	指数值(x)	等级划分
≥4	极端湿润	-1~-1.99	轻微干旱
3.00~3.99	严重湿润	-2.00~-2.99	中等干旱
2.00~2.99	中等湿润	-3.00~-3.99	严重干旱
1.00~1.99	轻微湿润	≤-4	极端干旱
-0.99~0.99	正常

	率定期				验证期
	Re/%		R²	E_NS	Re/%	R²	E_NS
华县站	10.07	0.85	0.83		12.38	0.68	0.70
咸阳站	-9.09	0.86	0.82		-11.70	0.68	0.67
魏家堡	12.65	0.67	0.60		-15.74	0.61	0.65
林家村	16.19	0.75	0.61		34.26	0.65	0.45

	轻微干旱			中等干旱		严重干旱			极端干旱
	月数		频率/%		月数	频率/%	月数	频率/%	月数	频率/%
渭河流域	65	13.89		19	4.06	8	1.71		6	1.28
渭河干流	58	12.39		19	4.06	7	1.50		4	0.86
泾河流域	70	14.96		25	5.34	12	2.56		11	2.35
北洛河流域	53	11.33		30	6.41	10	2.14		4	0.85

Spatiotemporal patterns of droughts based on SWAT model for the Weihe River Basin

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 11

References 35

Related Articles 8

Metrics

Comments

Recommended 0

[1]	LI Runkui, ZHU A-Xing, LI Baolin, PEI Tao, QIN Chengzhi. Response of Simulated Stream Flow to Soil Data Spatial Detail across Different Routing Areas [J]. PROGRESS IN GEOGRAPHY, 2011, 30(1): 80-86.
[2]	FENG Xiaqing,ZHANG Guangxin,YIN Xiongrui. Study on the Hydrological Response to Climate Change in Wuyur River Basin Based on the SWAT Model [J]. PROGRESS IN GEOGRAPHY, 2010, 29(7): 827-832.
[3]	YE Xuchun1,2, ZHANG Qi1, LIU Jian1,2, LI Lijiao1,2, ZUO Haijun1,2 . Effects of Spatial Resolution of Soil Data on Hydrological Processes Modeling [J]. PROGRESS IN GEOGRAPHY, 2009, 28(4): 575-583.
[4]	ZHU Xinjun, WANG Zhonggen, XIA Jun, YU Lei. Basin Level Water Balance Analysis Study Based on Distr ibuted Hydrological Model ———Case Study in the Haihe River Basin [J]. PROGRESS IN GEOGRAPHY, 2008, 27(4): 23-27.
[5]	ZHU Xinjun,WANG Zhonggen,LI Jianxin,YU Lei,WANG Jingui. Applications of SWAT model in Zhang Wei River Basin [J]. PROGRESS IN GEOGRAPHY, 2006, 25(5): 105-111.
[6]	YANG Guilian, HAO Fanghua, LIU Changming, ZHANG Xuesong. The Study on Baseflow Estimation and Assessment in SWAT——Luohe Basin as An Example [J]. PROGRESS IN GEOGRAPHY, 2003, 22(5): 463-471.
[7]	LIU Changming, LI Daofeng, TIAN Ying, HAO Fanghua, YANG Guilian. An Application Study of DEM Based Distributed Hydrological Model on Macroscale Watershed [J]. PROGRESS IN GEOGRAPHY, 2003, 22(5): 437-445.
[8]	ZHU Xinjun, WANG Zhonggen, XIA Jun, YU Lei. Basin Level Water Balance Analysis Study Based on Distr ibuted Hydrological Model ———Case Study in the Haihe River Basin [J]. PROGRESS IN GEOGRAPHY, 0, 0(): 23-27.