地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (9): 1817-1834.doi: 10.12082/dqxxkx.2022.220356
收稿日期:
2022-06-27
修回日期:
2022-08-15
出版日期:
2022-09-25
发布日期:
2022-11-25
作者简介:
吕爱锋(1977— ),男,山东莱芜人,副研究员,博士,主要研究方向为水文水资源。E-mail: lvaf@igsnrr.ac.cn
基金资助:
LV Aifeng1,2,*(), QI Shanshan1,2
Received:
2022-06-27
Revised:
2022-08-15
Online:
2022-09-25
Published:
2022-11-25
Contact:
LV Aifeng
Supported by:
摘要:
山区降水较集中,但降水测站多位于山谷或人口密集区,代表性差。遥感和再分析降水产品能提供时空分布连续的数据,不受地形条件限制。柴达木盆地中心属干旱荒漠区,水是制约该区开发的首要条件,其四周属高寒山区,降水相对较多,但降水监测十分薄弱。为获取该区相对精确的降水时空分布信息,本文评估了4套高分辨率降水产品(CMADS、TRMM、GPM和MSWEP)的适用性。首先基于地面站点数据评估它们在不同时空尺度上的精度,并分析它们在柴达木盆地的空间分布和年内分配特征。然后,以盆地东南隅的无测站山区香日德河流域为研究区,利用降水产品驱动SWAT模型来评估它们的分布式水文模拟适用性。结果表明:① MSWEP在年、月尺度上与站点降水的吻合程度最高(R ≥ 0.79,PBIAS = 0.5%),其次是GPM和TRMM,CMADS精度最低(R ≥ 0.64,PBIAS = 5.8%);② 从降水精度与站点高程的关系来看,降水产品在相对低海拔区容易高估站点降水,而在相对高海拔区常低估实际降水;③ 在香日德河流域,MSWEP(NSE = 0.64)在基准期(2009—2012年)的径流模拟表现明显好于其它降水产品(NSE = 0.36~0.59),变化期(2013—2016年)表现最好的是CMADS(NSE = 0.75,其余产品NSE = 0.53~0.68)。本研究可为缺资料干旱山区获取精确的降水时空信息和后续水资源的科学管理与规划提供重要支撑。
吕爱锋, 亓珊珊. 遥感及再分析降水产品在缺资料干旱内陆盆地的适用性评估[J]. 地球信息科学学报, 2022, 24(9): 1817-1834.DOI:10.12082/dqxxkx.2022.220356
LV Aifeng, QI Shanshan. Applicability Analysis of Satellite-based and Reanalysis Precipitation Products in Poorly-Gauged Arid Inland Basins[J]. Journal of Geo-information Science, 2022, 24(9): 1817-1834.DOI:10.12082/dqxxkx.2022.220356
表1
柴达木盆地地面测站基本信息
类别 | 站名 | 纬度/°N | 经度/°E | 海拔/m | 月均降水量/mm |
---|---|---|---|---|---|
气象站 | 大柴旦 | 37.85 | 95.35 | 3179 | 8.4 |
德令哈 | 37.38 | 97.36 | 3001 | 19.5 | |
都兰 | 36.29 | 98.09 | 3185 | 20.1 | |
格尔木 | 36.42 | 94.90 | 2809 | 4.2 | |
冷湖 | 38.74 | 93.33 | 2765 | 1.8 | |
茫崖 | 38.25 | 90.85 | 2938 | 4.4 | |
诺木洪 | 36.43 | 96.42 | 2767 | 5.1 | |
乌兰 | 36.93 | 98.48 | 2980 | 19.6 | |
小灶火 | 36.80 | 93.68 | 2779 | 2.6 | |
水文站 | 察汗河 | 36.94 | 98.48 | 2957 | 39.3 |
察汗乌苏 | 36.24 | 98.11 | 3240 | 20.9 | |
德令哈(三) | 37.38 | 97.43 | 3025 | 21.9 | |
都兰雨量站 | 36.29 | 98.09 | 3194 | 21.2 | |
尕海 | 37.22 | 97.44 | 2860 | 13.2 | |
怀头他拉 | 37.34 | 96.73 | 2848 | 9.2 | |
上尕巴 | 36.99 | 98.57 | 3135 | 28.4 | |
夏日哈 | 36.40 | 98.12 | 3104 | 23.3 | |
香日德 | 35.91 | 97.98 | 3199 | 23.9 | |
纳赤台 | 35.87 | 94.57 | 3559 | 16.3 | |
柯尔 | 35.94 | 97.70 | 3249 | 26.3 | |
格尔木(四) | 36.31 | 94.78 | 2919 | 5.4 | |
千瓦鄂博 | 35.75 | 98.13 | 3453 | 14.0 |
表3
降水产品在香日德河流域基准期和变化期径流模拟最优参数
基准期 | 变化期 | |||||||
---|---|---|---|---|---|---|---|---|
CMADS | TRMM | GPM | MSWEP | CMADS | TRMM | GPM | MSWEP | |
CN2 | 39.45 | 69.04 | 41.46 | 38.18 | 59.60 | 63.49 | 61.64 | 35.02 |
ESCO | 0.34 | 0.58 | 0.57 | 0.66 | 0.02 | 0.18 | 0.83 | 0.71 |
EPCO | 0.48 | 0.61 | 0.64 | 0.58 | 0.97 | 0.16 | 0.02 | 0.73 |
OV_N | 0.47 | 0.15 | 0.41 | 0.59 | 0.36 | 0.20 | 0.57 | 0.23 |
CH_N2 | 0.02 | 0.47 | 0.34 | 0.32 | 0.22 | 0.20 | 0.04 | 0.31 |
CH_K2 | 9.55 | 64.55 | 74.94 | 6.41 | 20.57 | 18.03 | 149.07 | 53.26 |
ALPHA_BF | 1.00 | 1.00 | 0.31 | 0.09 | 1.00 | 1.00 | 0.32 | 0.99 |
GW_DELAY | 292.36 | 499.14 | 192.72 | 448.97 | 410.04 | 499.97 | 119.52 | 499.69 |
RCHRG_DP | 0.63 | 0.61 | 0.55 | 0.24 | 0.45 | 0.67 | 0.27 | 0.34 |
GW_REVAP | 0.05 | 0.03 | 0.09 | 0.14 | 0.10 | 0.04 | 0.19 | 0.14 |
GW_SPYLD | 0.20 | 0.26 | 0.16 | 0.30 | 0.11 | 0.24 | 0.35 | 0.30 |
SOL_AWC | 0.01 | 0.02 | 0.03 | 0.02 | 0.01 | 0.03 | 0.01 | 0.02 |
SOL_K | 52.06 | 24.38 | 43.17 | 21.39 | 27.94 | 20.85 | 32.85 | 18.87 |
SURLAG | 3.60 | 10.06 | 5.82 | 5.04 | 7.27 | 11.11 | 3.15 | 11.49 |
NSE | 0.35 | 0.58 | 0.51 | 0.64 | 0.75 | 0.68 | 0.53 | 0.64 |
PBIAS/% | 0 | 0 | 0 | 0 | 0.1 | -0.1 | 0 | -0.1 |
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[1] | 侯玥, 徐成东, 刘伟, 殷倩. 气候变化情景下淮河上游流域氮排放预测研究[J]. 地球信息科学学报, 2022, 24(8): 1558-1574. |
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