Palaeoflood simulation of the Kamo River basin using a grid-cell distributed rainfall run-off model

2013 ◽  
Vol 7 (2) ◽  
pp. 182-192 ◽  
Author(s):  
P. Luo ◽  
K. Takara ◽  
Apip ◽  
B. He ◽  
D. Nover
Keyword(s):  
2011 ◽  
Vol 8 (1) ◽  
pp. 763-809 ◽  
Author(s):  
M. M. Mekonnen ◽  
A. Y. Hoekstra

Abstract. This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment is global and improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc min grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the water footprint network. Considering the water footprints of primary crops, we see that global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals} (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78% green, 12% blue, 10% grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45% of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus River Basin (117 Gm3 yr−1) and the Ganges River Basin (108 Gm3 yr−1). The two basins together account for 25% of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91% green, 9% grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48% green, 40% blue, 12% grey).


1987 ◽  
Vol 9 ◽  
pp. 225-228
Author(s):  
Zeng Qunzhi ◽  
Zhang Shunying ◽  
Chen Xianzhang ◽  
Wang Jian

The images of NOAA/TIROS-N APT, AVHRR and a few Landsat MSS obtained from 1980 to 1985 are analysed in this paper. It is found that the snow-cover distribution in Qilian Mountains is above 3700 m a.s.l. during winter to spring every year. There are two concentrations of snow cover. One is on Mount Leng Longling in the upper reaches of the Shiyang River and the other is located between Hala Lake and Mount Danghe Nanshan.Based on preliminary investigations, it is known that the surface water resource in the Hexi region is 68 8 × 108 m3, of which about 24.8% is from glaciers and melting, and the snow-melt run-off is 7.63 × 108 m3, equal to 62.6% of the total amount of spring run-off.The average value of Cv for spring run-off in the Shiyang River, Heihe River, and Shule River is 0 32 and the Cv value of snow-melt run-off in spring is 0.41, about three times as much as that of the annual run-off in the Hexi, region. A prediction model of spring snow-melt run-off at the Ying Louxia Hydrometric station in the Heihe River area can be constructed by using hydrometeorological data and snow-cover percentage for the Heihe River basin obtained from NOAA/TIROS-N APT, and AVHRR images. The prediction models (2) and (3) have been tested by the Water Resources Management Office of the Heihe River basin in the Zhangye and Flood Prevention Office of Gansu Province. The prediction accuracy is suitable for demands.


2019 ◽  
Vol 9 (18) ◽  
pp. 3690 ◽  
Author(s):  
Daeryong Park ◽  
Huan-Jung Fan ◽  
Jun-Jie Zhu ◽  
Sang-Eun Oh ◽  
Myoung-Jin Um ◽  
...  

This study analyzed the result of parameter optimization using the digital elevation model (DEM) resolution in the TOPography-based hydrological MODEL (TOPMODEL). Also, this study investigated the sensitivity of the TOPMODEL efficiency by applying the varying resolution of the DEM grid cell size. This work applied TOPMODEL to two mountainous watersheds in South Korea: the Dongkok watershed in the Wicheon river basin and the Ieemokjung watershed in the Pyeongchang river basin. The DEM grid cell sizes were 5, 10, 20, 40, 80, 160, and 300 m. The effect of DEM grid cell size on the runoff was investigated by using the DEM grid cell size resolution to optimize the parameter sets. As the DEM grid cell size increased, the estimated peak discharge was found to increase based on different parameter sets. In addition, this study investigated the DEM grid cell size that was most reliable for use in runoff simulations with various parameter sets in the experimental watersheds. The results demonstrated that the TOPMODEL efficiencies in both the Dongkok and Ieemokjung watersheds rarely changed up to a DEM grid-size resolution of about 40 m, but the TOPMODEL efficiencies changed with the coarse resolution as the parameter sets were changed. This study is important for understanding and quantifying the modeling behaviors of TOPMODEL under the influence of DEM resolution based on different parameter sets.


2016 ◽  
Vol 48 (1) ◽  
pp. 191-213 ◽  
Author(s):  
Lei Li ◽  
Zongxue Xu ◽  
Jie Zhao ◽  
Longqiang Su

A Grid-based Integrated Surface–Groundwater Model (GISMOD) was developed to estimate the required irrigation water using a control-site method. The entire catchment is divided into multiple grid cells of equal size, and several grid cells can be chosen as the control sites by users in this model. The grid cells from the upper stream of each control site, which have a land-use type of farmland, are automatically identified as a controlled grid cell. The crop information around each controlled grid cell is set to be the same as its corresponding control site. Next, the irrigation water requirement for each controlled grid cell is calculated using a crop coefficient method that is integrated into the human water-use module of the GISMOD. After runoff is generated, the actual discharge of each control site is computed by comparing the available water sources with the irrigation water requirement based on the water-supply operation rules of the model. This paper subsequently presents a case study in the upper-middle reaches of the Heihe River to evaluate the performance of the GISMOD. The results demonstrate that the actual water consumption for irrigation in the Heihe River basin could be generally estimated by the GISMOD on a monthly basis.


2020 ◽  
Vol 34 (8) ◽  
pp. 1906-1919
Author(s):  
Xiaonan Yang ◽  
Wenyi Sun ◽  
Xingmin Mu ◽  
Peng Gao ◽  
Guangju Zhao

Author(s):  
S. M. Wahid ◽  
A. B. Shrestha ◽  
M. S. R. Murthy ◽  
M. Matin ◽  
J. Zhang ◽  
...  

The Hindu Kush Himalayan (HKH) region is the source of ten large Asian river systems – the Amu Darya, Indus, Ganges, Brahmaputra (Yarlungtsanpo), Irrawaddy, Salween (Nu), Mekong (Lancang), Yangtse (Jinsha), Yellow River (Huanghe), and Tarim (Dayan), - and provides water, ecosystem services, and the basis for livelihoods to a population of around 0.2 billion people in the region. The river basins of these rivers provide water to 1.3 billion people, a fifth of the world’s population. Against this background, a comprehensive river basin program having current focus on the Koshi and Indus basins is launched at the International Center for Integrated Mountain Development (ICIMOD) as a joint scientific endeavour of several participating institutions from four regional countries of the HKH region. The river basin approach aims is to maximize the economic and social benefits derived from water resources in an equitable manner while conserving and, where necessary, restoring freshwater ecosystems, and improved understanding of upstream-downstream linkages. In order to effectively support river basin management satellite based multi sensor and multi temporal data is used to understand diverse river basin related aspects. We present here our recent experiences and results on satellite based rainfall and run off assessments, land use and land cover change and erosion dynamics, multi thematic water vulnerability assessments, space based data streaming systems for dynamic hydrological modelling, and potential applications of agent based models in effective local water use management.


Author(s):  
R. Khasiev

China’s habitually closed water policy in the region of South-Еast Asia has strained its relations with the six countries of the Mekong-river basin. The Chinese government has been intentionally concealing its water management plans, which has sparked off a clash of interests between China and most SEA nations. The “dams policy” pursued by China enabled the country to take the Mekong run-off under control. At the same time, it has greatly affected the country’s international image, making China look like a regional bully.


2020 ◽  
Author(s):  
HM Mehedi Hasan ◽  
Andreas Güntner ◽  
Somayeh Shadkam ◽  
Petra Döll

<p>The predictive ability of a hydrological model depends among others on how well the model is calibrated by model parameter adjustment. When calibrating spatially distributed models such as global hydrological models in which river basins are represented by laterally connected grid cells of mostly 0.5° latitude by 0.5° longitude, it is not appropriate and possible to adjust the parameters of each grid cell individually. This is mainly due to the lack of high-resolution observations but also due to the required computational effort. It needs to be investigated which spatial extent of calibration units for which parameters are uniformly adjusted, is optimal given the available observations and the characteristics of the region or river basin. To explore the effect of size and number of calibration units, the WaterGAP Global Hydrological Model (WGHM) was calibrated for a large river basin in North America, the Mississippi basin, successively dividing the basin into smaller calibration units, i.e., sub-basins, in order to examine the feasibility and value of reducing the size of calibration units for the given set of observations. Total water storage anomalies from GRACE satellites, snow cover from MODIS and in-situ streamflow were used as observations in an ensemble-based multi-criterial Pareto Optimization Calibration (POC) framework using the Borg-MOEA optimization algorithm.</p>


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