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A Distribution Hydrological
Modeling Applied to Heihe Basin in Western China
Jun Xia 1,2, Gangsheng Wang 1, Ge Tan1
1. Institute of Geographical Sciences and Natural Resources Research,
CAS, Beijing 100101, China
2. Wuhan University, Wuhan 430072, China
Email: jxia_mail@263.net
The Western China Development is confronted with a quite serious and
realistic problem on water resources because of the water cycle's
district characteristics, the ecosystem's vulnerability and the increasing
demand of water resources. Based on the traits and existent problem
of water cycle in western China, the key scientific issues of water
cycle in western China has been studied in this paper. Main contribution
in this paper is to develop a distributed hydrological modeling coupled
physical process grids with a Time Vafian Gain Model (TVGM) that was
developed for system approach in University College of Galway, Ireland
for river flow forecasting (1995). This model has three advantages:
(a) It can be available to the case of input information imperfection
such as the lack of enough precipitation and evaporation observations
for distribution modeling;
(b) It can be coupled the present physical process units or conceptual
models with hydrological system approach such as TVGM, where time
variant gain factor, G (t), could be linked with RS information to
extend easily to application of hydrological prediction in basin scale;
(c) Parameter sets of the distributed hydrological model can be estimated
in terms of system identification approach to reduce uncertainty
By preliminary application and examination in the Heihe River Basin
of Guansu Province with area 1300km2 in arid & semi arid region,
it was found that this model is successful with more advantages than
conditional distributed model applied in China. Moreover, the new
problems were addressed in the paper.
A Distributed Runoff Model for Inland River Mountainous Basin of
Northwest China
Rensheng Chen, Ersi Kang, Jishi Zhang
Cold and Arid Regions Environment and Engineering Research Institute,
Chinese Academy of Sciences, Lanzhou Gansu 730000, China
E-mail: crs2008@ns.lzb.ac.cn
The Arid Area of Northwest China lies in the inland area of Asia far
from oceans. It consists of several large inland river basins. Many
enormous mountain ranges lie in the area and uplift the air current
containing water vapor, making the mountainous area receive much more
precipitation compared with the low land area in front of the mountains.
Glaciers and snow storage develop very well in the mountains. Therefore,
in an inland basin of Northwest China, mountainous watersheds are
runoff generation areas, while the low land plains, basins and deserts
in front of the mountains are the area of water resources consumption
and runoff scattering. Thus, the runoff amount generated from the
mountains, which run out off outlets of the mountainous watersheds,
basically represents the amount of water resources of the inland arid
area. Now the oases in Northwest China are diminishing, while the
deserts are expanding. Therefore, it is very significant to forecast
the runoff amount from mountainous area. For water management, environmental
conservation and other applications, monthly runoff amount forecasting
may be more important. As a case study, we tend to forecast the monthly
runoff from mountainous catchments of Heihe mainstream. Heihe River,
originating from the Qilian Mountains, running through the Hexi Corridor
and scattering in the deserts, is one of the largest inland rivers
in Northwest China, with a drainage area of 130,000 km2. Heihe river
basin, like other inland river basin in Northwest China, posses distinctive
vertical zonality of landscape: the mountainous area and the area
in front of the mountains. The former can be divided into the high
mountain ice, snow and permafrost zone and the mountain vegetation
zone, while the latter can be divided into oases zone and desert zone.
Distributed hydrological model has been studied worldwide, while rarely
used in large basin scale, because it requires too many parameters
and too many hydrologic data, meteorological data, soil data, vegetation
data etc. In this paper, the author want to use the routine hydrometeor
logic data to create a distributed model, coupled with GIS and RS
techniques and data. The model takes sub-basin as the minimal confluent
unit, divides the main soil of the basin into 3 layers, and divides
the vegetation type as forest and pasture. Because there is little
data required by the standard distributed model, this model gives
some conceptual parameters. The data used in the model are precipitation,
air temperature, runoff data, soil weight water content, soil depth,
soil bulk density, soil porosity, vegetation cover etc. The model
defines and introduces some concepts: soil volume water content, soil
water content capacity, soil water amount, and hold that if the water
amount is more than the water content capacity, there will be surface
runoff. The actual evaporation is proportional to the product of the
potential evaporation and soil volume water content. The studied basin
is Heihe mainstream mountainous basin, with a drainage area 10009
km2. The model time step is a month.
The data used in this simulation are 1980.1-1995.12, and are divided
into 2 parts. The first 10 years' data are used to simulate, while
the last 5 years' data are used to calibrate. The results are very
well. For the simulation process, the NSE (Nash-Sutcliffe Equation),
B (Balance Error) and EV (Explained Variance) are 0.8681, 5.4008 and
0.8718 respectively, while for the calibration process, the NSE, B
and EV is 0.8799, -0.5974 and 0.8800 respectively. Thus, the model
has been successfully used in Heihe mainstream mountainous watershed.
The results show that, the vegetation, especially the forest in Heihe
mountainous watershed, could decrease the evapotranspiration of the
watershed, adjust the runoffprocess, and could increase the soil water
content.
Analysis of Relation Between Plant Ecosystem and
Shallow Groundwater
Flow System in Ejina Catchment of Downstream Heihe Basin
Yanqing Wu1,2
1. CoM and Arid Regions Environmental and Engineering Research Institute
of CAS, Landzhou 730000, China
2.Xi 'an University of Technology, Xi 'an China
Email: yqwu@ns.lzb.ac.cn
The study area is located the downstream Heihe basin, arid region
inland river watershed, northwest of China. In recent 30 years, the
desert oasis has degenerated because unreasonable use of water resources
in the middle Heihe basin has resulted in the decrease of the downstream
river discharge and the decline of groundwater level. Through site
investigation of desert plant ecosystem, soil moisture and groundwater
level in phreatic aquifer, we have found that the close connection
between desert plant ecosystem and groundwater system.
According to the observation data of groundwater level and analysis
of remote sensing images, the change relation between desert plant
ecosystem and shallow groundwater level has studied in regional scale
and proposed that river runoff entering downstream basin needs 7.5¡Á108m3/a
to protect the safety of existing desert plant ecosystem.
Analysis of the Interaction Between Groundwater and Surface Water
Using
Radon-222 in Middle Heihe Basin of Northwestern China
Yanqing Wu1,2:
1. Cold and Arid Regions Environmental and Engineering Research Institute
of CAS, Landzhou 730000, China
2. Xi 'an University of Technology, Xi 'an China
Email: yqwu@ns.lzb.ac.cn
In arid regions of western China, water resources come from mountain
watershed and disappear in desdrt plain. The exchange of surface water
and groundwater takes place 2 or 3 times in a basin. It is essential
to analyze the intdraction between groundwater and surface water in
order to use water resources effectively and predict the change of
water environment. The conventional method of analysis, however, measures
only the flow of a stream and cannot determine groundwater seepage
accurately. Since the concentration of Radon-222 (222Rn) in groundwater
is much higher than in surface water, the use of 222:Rn was examined
as an indicator for the analysis of the interaction between surface
water and groundwater. Measurement of the 222Rn concentration in surface
water was conducted to detect groundwater seepage into a stream in
middle Heihe basin. Furthermore, the simultaneous movement of water
both into and out of a stream from the underlying strata was quantified
by solving the 222Rn and water balance equations. Meanwhile, river
runoff was gauged to determine the exchange rates between surface
water and groundwater.
Application of the AnnAGNPS Model with GIS Interface to Erosion
Accounting for Watershed
Ming-Shu Tsou1 and Xiaoyong Zhan1 ,Changyuan Tang2
,Junhong Chen3
1. Kansas Geological Survey, Lawrence Kansas 66047, USA. Lyle Frees
and Chad Volkman, US Departmdnt of Agriculture, NRCS, USA
2. Graduate School of Science and Technology, Chiba University, 1-33
Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
3.Institute of Geography, Guangzhou, China
Email: xyz@ku.edu
Water availability and quality in many watersheds are becoming a threat
to food security, human health, and the natural ecosystem. Watershed
management depends on monitoring and modelling of watershed. This
paper reports the progress of watershed modelling with emphasis on
sediment transport in the Cheney watershed, Kansas by using the continuous-simulation
Annualised Agricultural Nonpoint Source Pollution (AnnAGNPS) model
with GIS interface developed recently.
Annualized Agricultural Nonpoint Source Pollution Modeling System
(AnnAGNPS) is a joint colputer model of the USDA Agricultural Research
Service and Natural Resources Conservation Service, and was developed
to predict nonpoint-source pollutant loadings within agricultural
watersheds. It is a popular model in surface hydrology in the USA
and other countries. Water, sediment, and chemicals (nutrients and
pesticides) are simulated leaving land areas (cells), flowing into
the watershed-stream network at user-specified locations (reaches),
and eventually arriving at the watershed outlet on a daily basis as
final output of the model.
The first part of this paper provides an integrated overview of the
multiple facets of watdrshed modeling-GIS-database issues of AnnAGNPS.
A newly implemented enhanced GIS interface is discussed briefly. This
ArcView extension facilitates the modeling exercise for AnnAGNPS.
Also, an approach to fully use Soil Survey Geographic (SSURGO), one
of national standard soil databases, was developed for AnnAGNPS.
The second part of the paper presents an application of AnnAGNPS to
the Cheney reservoir watershed in south-central Kansas, USA. The watershed
covers approximately 989 square miles. Ninety-eight percent of the
watershed land is used as agricultural with varies farming practices.
The Cheney reservoir supplies over 60$ of the daily drinking water
to the City of Wichita. Last decade sediment loading in the Reservoir
was identified as one of the primary problems in this watershed. Result
of AnnAGNPS modeling provides a planning tool to make recommendations
for remedial action to improve and preserve the reservoir to its maximum
potential, to identify which best-management practices (BMPs) minimize
sediment load, and for assist in the development of a strategic plan
to accomplish the ultimate goal of cleaner water.
Finally, potential applications to watersheds in China and Japan are
briefly discussed because these two countries are strongly focusing
on long-term best-management practices in watersheds for maximum eco-environmental
benefit.
Assessment of the Indicators of Aridity for Uzbekistan
Related to Climate
Change
Spektorman T. Yu
Under current conditions, water resource shortages in Uzbekistan,
even a small but stable reduction of these resources presents a drastic
problem. During the course of the last third of the 20th century,
intensive irrigation from the flows of the Central Asian rivers caused
the regrettable Aral Sea crisis: the drying-up of the Aral Sea, a
reduction of the delta lakes and drastic aggravation of the ecological
situation in the Aral Sea Region
Such factors as drought and human-induced changes
(the existing irrigation practice and the global warming) are inter-related;
this leads to increasing negative impact.
Climate study has shown that changes in various components of the
climate system are already underway in the region. Wanning tendencies
during both the cold and warm seasons have been observed. Observations
in the mountain river basins demonstrate a stable decrease of snow
cover. The degradation of glaciers is evident, as well as a reduction
in over-all glacial areas. From other side the monitoring data of
the past 70 years do not show any significant tendencies towards change
in the precipitation regime in the territory of Uzbekistan.
Comparison of Regional Flood Estimation Models Over
Some Catchments
in Kenya
Paul Ng'ala O1oo, Prof. Francis M. Mutua, Prof. Laban
A. Ogallo
Many annual flood data are too short to allow for reliable estimation
of extreme events. Big portions of most river basins are not gauged,
yet design floods are needed at ungauged sites. Such short records
further contain outlying flood values, which makes estimates of floods
of a given return period to be highly uncertain. The short period
data can also lead to different cumulative distribution functions
to be fitted to stream flow data of neighboring gauges with the same
hydrological characteristics.
Adopting regional flood frequency analysis can minimize some of these
flood frequency problems. In such analyses, hydrologic information
from several gauging stations is combined to provide regionally averaged
hydrological information. This can improve or stabilize site-specific
estimates based on limited site data. Regional information can also
be used to estimate design flood at ungauged river basins, by using
models, which can transfer regional information into site-specific
information.
Regional flood estimation procedures require the identification of
homogeneous regions. These regions were delineated for every basin
considered using the rotated solutions of Principal Component Analysis.
A comparison of regional flood estimation models was then undertaken
in this study and the basins targeted included the Lake Victoria,
Tana River and Athi River in Kenya and the models included the Index
flood, two component extreme value and empirical Bayes methods. The
data used in this study consisted of the annual maximum flood series
for sixty-one gauging stations for the period 1960 - 1994.
The General extreme value, two component extreme value and lognormal
distributions were the regional distributions used together with the
three regional flood estimation models. Their parameters were estimated
using the moments, maximum likelihood and probability-weighted moment's
methods. The performance of the best regional flood estimation model
was determined using the Kolmogorov-Smirnov test, Chi-square test
and Akaike Information Criterion. Simulation was further used to test
if the best regional distribution could provide skilful estimates
of floods over the homogeneous regions.
The results from the rotated solutions of Principal Component Analysis
showed that the three drainage basins could be grouped into nine homogeneous
flood regions with three regions in the Lake Victoria basin, four
regions in the Tana River basin and two regions in the Athi River
basin. The nine groups that were derived formed the fundamental basis
for the development of the regional flood estimation models, which
were used in this study.
The results from the Index flood method indicated that, the extreme
value type 2 was identified as the regional distribution that could
best fit annual flow records in all the drainage basins. The extreme
value type 1 could also be used predominantly in the Tana River basin.
The results also showed that the two-component extreme value distribution
was inappropriate for modeling annual maximum flows, since the extraordinary
flood events were very few in comparison to the ordinary flood events.
The empirical Bayes method parameter estimates had very large standard
errors, since the super population of flows based on regional regression
relationship is weak. The General extreme value distribution was the
best fitting regional distribution with the lognormal distribution
giving the worst fit. The general extreme value distribution was therefore
utilized in the simulation study. It was found that it could provide
skilful estimates for the flows in all the nine regions.
It may be concluded from this study that reliable estimates of design
flood can be obtained both for gauged and ungauged river basins by
regional flood frequency analysis. The Index flood method with the
General extreme value distribution was found to be the best regional
flood estimation method in this study. The empirical Bayes method
was the worst regional flood estimation method. The results from this
study can be used for the general planning and management of most
hydrological systems in Kenya.
Determination of Change Points in Nonlinear Hydrologic Time Series
Using
Fuzzy Statistical Approach
Simon Wu1 ,Gordon Huang2
1.Saskatchewan Agriculture and Food, Regina, Saskatchewan S4S OB1,
Canada
2. Faculty of Engineering, University of Regina, Regina, Saskatchewan,
S4S 0A2, Canada
Email: swu@agr.gov.sk..ca
Hydrologic time series models are valuable analytical tools for assessing
potential impacts of climate change on water resources systems. Most
analyses have been based on the assumption that there is a constant
regime throughout the temporal dimension. However, regional climate
shifts have been observed around the world for many years. Efforts
have been made to introduce change detection methodology to solving
the problem in the application of time series in water resources.
Change points are now normally searched and examined before time series
modeling is conducted. In addition to classical sequential analysis,
many innovative methods such as Bayesian estimation and Markov Chain
Monte-Carlo simulation have been proposed to deal with change detections
in the fields of engineering, financial mathematics and econometrics.
A common disadvantage with most of the methods is their incapability
of handling nonlinear models. Even more important is that those techniques
base their detection on an instant time point or relatively very short
period. Variations in phenomenon regime could thus be misidentified.
A fuzzy statistical approach is applied in this study to nonlinear
hydrologic time series analysis. Combining fuzzy clustering with a
current change detection procedure forms the approach. Fuzzy change
period concept in the form of a-level point is used to properly extend
the detection time points. The application of the method to time series
analysis for a river flow is presented in the paper. It shows the
technique can be used effectively to identify the change points. More
case studies are being undertaken to further examine its applicability
to predicting environmental changes.
Genetic Analysis of Yellow River Tidewater Inflow
Sharp-Reduction in 90s
Xuecheng Zhang, Ling Wang, Qimin Pan
Hydrology Bureau, YRCC, Zhengzhou 450003, China
Email: Xuecheng@371.net
Yellow River mean tidewater inflow in 90s is only 119.2 ¡Á 108 m3 which
took 32% of mean tidewater inflow before 90s. With considering rainfall,
human being activity such as water resources development and utilization,
ecological and environmental construction etc., this paper searches
about the causation of Yellow River tidewater inflow sharp-reduction
in 90s. The result shows that action of rainfall variety taking 36%
and action of human being activity taking 64%.
Human-induced Water Scarcity on Loess Plateau of
China
Xiubin He, Fengli Zheng, Mingde Hao, Keli Tang
Institute of Soil and Water Conservation, Chinese Academy of Sciences,
and Northwest Sci-Tech University of Agriculture and Forestry, Yangling
712100, China
Email: hexiubin@yahoo.com
Water scarcity is one of the most prominent issues of discussion worldwide
concerned with sustainable development, especially in the arid and
semi-arid areas. On the Loess Plateau of China, population growth
and fast-growing cities and industries have caused ever-increasing
competition for water. The present paper shows a down-scale analysis
on how the regionwide mass action of food-security-oriented soil-water
conservation ecologically influenced regional water scarcity on the
Loess Plateau, the Middle Reaches of the Yellow River of China. Result
shows a great progress has been achieved in erosion control and food
production since the 1980s. About 24% of erosion area has been controlled.
Grain yield has increased greatly and sediment in the Yellow River
has decreased by about 25%. However, various evidences show that the
soil-water conservation measures might have played a great role on
regional hydrocycles, leading the depletion of deep soil water, no
runoff in the Yellow River and consequently ecological problem. It
implies that cropland and artificial forestry are increasingly suffering
water stress ecologically. Advancing sustainable development further,
or even maintaining the current situation, will be a great challenge
given the burgeoning socio-economic development of the area combined
with global climatic change.
Modeling Soil Water Dynamic at Watershed Scale in
Hilly Area of Loess
Plateau, China
Hongmei Xu
The Institute of Resource Science of Beijing Normal University and
The Open Research Lab. of Environment Change and
Natural Disasters of the State Education Commission, Beijing 100875,
China
Email: xhm@irs.bnu.edu.cn
In arid and semiarid ecosystem of Loess Plateau of China, the average
soil moisture is quite low and the patterns of seasonal precipitation
and the quantity of soil water availability are highly variable. Because
of this, water is a major determination of ecosystem processes.
The hilly area of loess plateau is well known for its high erosion
rate. The hydrologic cycle in hilly area of loess plateau include:
1) low annual precipitation but high-intensity storms with significant
variability, 2) high potential evaporation according to the high radiation
and poor soil retention capacity 3) The groundwater don't include
in hydrologic cycle because of the deep water table and the thick
loess soil profile, 4) Surface runoff is mainly produced by infiltration
exceed overland flow. All of these showed that rainfall is the main
replenishment of soil water. So the ecosystem is particularly vulnerable
to climate change, especially the variation of precipitation. A slight
change in annual rainfall or the distribution of seasonal precipitation,
or the frequency of extreme rain event could produce major ecological
impacts. Therefore, modeling soil water dynamic with precipitation,
radiation and other micro-environment elements based on the basic
principle of the balance of water and energy, simulating the soil
moisture spatial distribution at watershed scale according to runoff
processes are very important for the arid and semi-arid ecosystem
of loess plateau.
In this article we developed a daily time step, multi-horizon, distributed
spatial model (SWDM - Soil Water Dynamic Model) to explore the spatial
and temporal variability of soil water content determined by the hydrological
characteristic of soil, precipitation and vegetation coven In SWDM,
soil water is represent in 4 layers (the top layer-20cm, the second-40cm,
the third layer-40cm, the bottom layer-100cm). Infiltration adds water
to soil layers in a cascading fashion according to water holding capacities
of layers and the redistribution among the layers defined as Darcy-Richards
equation. No infiltration beyond 2m and no horizontal water movement
is taken into account. Water is removed from the top layer by evaporation
and from all layers by transpiration. The potential evapotranspiration
was calculated by Penman-Montieth equation. Removal of water via evaporation
was determined by energy to the surface layer and the total leaf area
of vegetation. Removal of water via transpiration form soil is partitioned
among the layers according the distribution of total roots in each
layer and related to the total leaf area of vegetation and the transpiration
capacity of the plant canopy. Calculations of runoff and run-on flows
are important for a watershed scale simulation model, as the flows
represent important spatial processes in a watershed. Runoff was generated
when total rate of rainfall is larger than the steady penetrating
rate and the surface soil gets saturated. Runoff from a grid cell
is distributed to one of its neighborhood cells with lower elevation.
Run-on to a grid cell is simply summation of surface runoff from higher
neighboring grid cells.
The model was tested in Zhifanggou watershed, which belongs to Ansai
city and covers an area 8.27Km2.The regional topographic types are
loess hilly and gully landforms. The soil has developed over loess
with fine silt to slit in texture, and slope vary between 10-30~.
The present vegetation cover of the study area is composed mostly
of natural grassland, artificial shrub, woodland and farmland. Climate
variables and vegetation cover pattern were used as input driving
variables for the model. In the modeling experiment, SWDM simulations
have been shown to provide good approximation with field observation
data.
On the Accuracy of Spherical Gages for Rainfall Measurements
Mingteh Chang1, Lee Harrison2
1. Arthur Temple College of Forestry Stephen E Austin State University.
Nacogdoches, Texas 75962-6109, USA
2. Meteorologist-in-Charge, US National Weather Service Shreveport,
Louisiana 71109- 7750, USA
Email: F_ changmi@sfasu.edu
Because of wind effects, point rainfall measurement is always deficient
and a 10% error of rainfall input may result in a 15-30% error in
runoff output in hydrologic simulations. Two spherical orifices were
designed to modify the standard gage and other gages in use today
(Chang and Flannery, 2001). Because of the spherical shape, the two
orifices will catch rain with an effective diameter always equal to
the actual diameter regardless of wind speed and direction. This reduces
wind effect on rainfall catch to a minimum level. This report tested
the spherical gages at two different locations, one at the City Landfill,
Nacogdoches, Texas and the other at the NWS Forecast Office, Shreveport,
Louisiana. Based on 131 storms at Nacogdoches and 94 storms at Shreveport
observed between May 1998 and February 2001, the results showed: 1)
spherical gages recorded an average 6-9% greater than standard gage
and 3-4% less than pit gage, only 1-2% less than reported in the original
study, 2) the catch of spherical gages was not significantly affected
by three gage heights at 0.91, 1.83, and 2.74 m above the ground,
but catch by the standard gage decreased with increasing gage height,
3) improvements of the spherical gages were most significant for larger
storms and for winds at higher speeds, 4) the spherical gage with
cylinders recorded 1-2% more rainfall than the spherical gage with
vanes, and 5) correlation coefficients between catch deficiencies
and wind speed were low and weak because of the distance and height
of the existing wind sensor.
Due to greater surface wetting and evaporation loss, the spherical
gages may underestimate rainfall catch by standard gage for small
storms (generally less than 0.50 cm), especially in hot summer afternoon
and for smaller storms. However, the underestimates do not over-shadow
the merits of spherical gages because the differences are too small
to be of hydrologic significance. Using polyethylene or other synthesized
materials to construct spherical orifices may improve the catch for
small storms. The results of the study agreed with the previous claims
that spherical gages are effective in reducing wind effects on rainfall
measurements and are suitable for large-scale applications.
Research on the Flood Forecast Model of Nonlinear
Runoff and
Concentration for Luhun Reservoir
Xingyuan Song1, Shenglian Guo1, Zhicheng Su1, Yong
Du1, Bei Wang1
Huale Jia2, Mibo Sun2, Yansheng Wang2, Jingwei Hao2
1. School of Water Resources and Hydropower, Wuhan University, Wuhan
430072, China
2. The department of Luhuen Reservoir Luoyang, Hunen 471000, China
Email: xysong@wuhee.edu.cn
The effects of basin nonlinear runoff and confluence are considered
from the basin rainfall space-time changes and the basin topography
as well as the river channel characteristics. This paper presents
the basin models of nonlinear runoff and confluence and the method
of real-time flood forecast. Using them to forecast the floods of
Luhun reservoir, it shows that the models and method are effective
in practice.
Sediment Yield Estimation in Cheney Watershed Using
Annagnps-gis
Modeling System
Ming-Sbu Tsou1, Xiaoyong Zhan1, Li Zheng1, Lyle Frees2
Chad Volkman2, Changyuan Tang3, Junhong Chen4
1.Kansas Geological Survey, Lawrence Kansas 66047, USA
2. US Department of Agriculture, NRCS, USA
3. Graduate School of Science and Technology, Chiba Universityl-33
Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
4. Guangzhou Institute of Geography, Guangzhou, 510070 P.R. China
Email: Zhengli_usa@yahoo.com
Water availability and quality in many watersheds are becoming a threat
to food security, human health, and the natural ecosystem. Watershed
management depends on monitoring and modeling of the watershed. This
paper reports the progress of watershed modeling with emphasis on
sediment transport in the Cheney watershed, Kansas, by using the continuous-simulation
Annualized Agricultural Nonpoint Source Pollution (AnnAGNPS) model
with GIS interface developed recently.
The first part of this paper provides an integrated overview of the
multiple facets of watershed modeling-GIS-database issues ofAnnAGNPS.
A newly implemented enhanced GIS interface is discussed briefly. This
ArcView extension facilitates the modeling exercise for AnnAGNPS.
Also, an approach to fully use Soil Survey Geographic (SSURGO), one
of national standard soil databases, was developed for AnnAGNPS.
The second part of the paper presents an application of AnnAGNPS to
the Cheney reservoir watershed in south-central Kansas, USA. Last
decade sediment loading in the reservoir was identified as one of
the primary problems in this watershed. Result of AnnAGNPS modeling
provides a planning tool to make recommendations for remedial action
to improve and preserve the reservoir to its maximum potential, to
identify which best-management practices (BMPs) minimize sediment
load, and to assist in the development of a strategic plan to accomplish
the ultimate goal of cleaner water.
Finally, potential applications to watersheds in China are briefly
discussed because this country is strongly focusing on long-term best-management
practices in watersheds for maximum eco-environmental benefit.
Simple Methods of Hydrological Data Provision for
Gauged and Ungauged
Catchments and Their Application in Developing Countries
Vladimir. U. Smakhtin
International Water Management Institute, PO Box 2075, Colombo, Sri
Lanka
Email: v.smakhtin@cgiar.org
The need for continuous stream flow time series is constantly increasing
with increasing pressure on water resources and emerging concepts
of environmental flow management in many parts of the world. The conventional
way of generating stream flow time series at ungauged sites in river
catchments and under different scenarios of catchments development
is through the use of deterministic rainfall runoff models, which
represent a flexible but information consuming and labor intensive
approach. In many developing countries, the input information required
to run a detailed rainfall-runoff model may simply not be available
and consequently, the use of such techniques may not necessarily result
in a reliable output. In such circumstances, the use of simpler and
quicker estimation methods may be more justified and, at the same
time, equally successful.
This paper intends to illustrate the pragmatic alternative to deterministic
modeling, which may be particularly relevant in data poor regions.
The approach is based on a Flow Duration Curve (FDC) - a cumulative
distribution of stream flow values and a graphical summary of stream
flow variability at a site. The ultimate goal in pragmatic hydrological
modeling concept is the same as in any catchments modeling - a continuous
stream flow time series, representing a catchments hydrological response
under natural condition or under certain scenario of development.
The calculation of representative FDCs is the prerequisite for it
and the starting point. The shape of the curve is determined by rainfall
pattern, catchments size and physiographic characteristics, land-use
type and the state of the water resource development. The effects
of these factors on stream flow may therefore be built in the curve
itself, prior to the simulation of actual continuous stream flow time
series. In general, the methodology of pragmatic hydrological time
series modeling includes:
Technique(s) by which to establish representative FDCs for different
types of river catchments in natural conditions. "Natural"
FDCs represent reference conditions of stream flow variability in
a catchments, which existed prior to any catchments or water resources
development. These techniques normally involve methods of hydrological
regionalisation
Technique(s) by which to adjust the "natural" FDCs to match
with the current state or possible scenarios of catchments and/or
water resources development. These techniques allow different catchments
development scenarios to be simulated (which also represent one of
the goals of conventional hydrological modeling). These techniques
involve correction of discharges of different exceedence values to
account for effects of catchments development, such as irrigation,
commercial forestry etc.
Technique(s) by which the established and adjusted FDCs may be transformed
into actual continuous flow time series for any further analysis.
The latter group of methods is built around a non-linear spatial interpolation
technique, which is based on the assumption that flows occurring simultaneously
at sites in a reasonably close proximity to each other correspond
to similar percentage points on their respective FDCs. The technique
is designed to generate continuous flow time series at a (destination)
site using either available flow data from the nearby (source) stream
flow gauges or rainfall data from rain gauges in catchments. For each
selected source site and for the destination site, tables of discharge
values are generated for each month of the year (or for the whole
year) for the 17 fixed percentage points on the corresponding FDC.
Following the main assumption of the algorithm, the core of the computational
procedure includes the estimation of the percentage point for each
day's flow at the source site and the identification of flow for the
equivalent percentage point from the destination site's FDC. The discharge
tables are used to "locate" the flows on corresponding curves
and log-interpolation is used between fixed percentage points. If
several source sites are used, the procedure is repeated for each
of them and the final destination discharge value on that day is calculated
as a weighted average of values obtained using individual source sites.
If no suitable source sites with observed flow data are identified,
the use may be made of rainfall records. If the source data from rain
gauge(s) are used, the source flow time series is replaced by the
time series of precipitation index, which reflects the current status
of catchments wetness. This "current precipitation index"
(CPI) is defined as a continuous function of precipitation, which
cumulates in rainy days and exponentially decays during the periods
of no rainfall. The process of rainfall-to-runoff conversion is then
based on the assumption that current precipitation index values at
rainfall site(s) in catchments and stream flow discharges at a destination
site correspond to similar probabilities on their respective duration
curves. AFDC at the ungaged destination site is established by regionalisation
methods.
The pragmatic hydrological modeling has a limited number of parameters.
It is transparent, simple to use, time efficient, not regionally restricted
and is applicable for generation of both daily and monthly flow data.
It could be used for hydrological time series patching and extension,
for the restoration of natural daily stream flow time series in already
modified catchments (for example in projects related to estimating
ecological in stream flow requirements), for generation of inflows
to coastal lagoons and estuaries, for data generation in ungagued
catchments, etc. The paper presents examples of application of pragmatic
time series modelling concept in several developing countries including
South Africa, Sri Lanka and Nepal.
Spatial Analysis of Rainfall Data Based on Self-Organizing
Competition
Neural Networks
Xiang Zhang, Jun Xia, Xingyuan Song
Department of Hydrology and Water Resource, College of Water Resources
and Hydropower, Wuhan University, Wuhan 430072, P. R China
Email: Scottzhx@yeah.net
The analysis of the spatial variability of rainfall has been of concern
to hydrologist for many decades. The methods of analysis include the
traditional methods such as Thiessen polygons, linear interpolation
based on distance between sites and geostatistical methods such as
Kriging. These traditional methods are mainly used to solve estimation
or interpolation problems; much less work is available to deal with
spatial classification problems. In this paper, we introduce a new
methodology, based on artificial neural networks, to characterize
spatial rainfall maps.
Artificial Neural Networks (ANNs) can be classified as two kinds such
as supervised and unsupervised networks by their training algorithm.
Self-organizing competition neural networks are belonging to the unsupervised
networks. Unlike feed-forward and recurrent neural networks that are
primarily used for approximation and optimization, self-organizing
competition neural networks are typically used for patterns classification
and projecting patterns from high dimensional to low dimensional space.
In this paper, a new kind of self-organizing competition neural networks
(SOCNNs) that hybrid ART II and Kohonen network is invested for classifying
the inherent space variability of rainfall data.
SOCNNS have two layers that are input and output layer respectively.
The input layer with n neural nodes passes the observed rainfall data
sets that are structured as the input vectors with subset consisting
of the daily elements. The neural nodes in output layer represent
the classes of rainfall. Their number will be determined as 1 at the
beginning of training. During the process of training, the number
of neural nodes in output layer will add 1 when one new class of rainfall
is found. After all the data sets are learned, the number of neural
nodes in output layer is the classes' number of rainfall. The space
distribution of different classes at the observing area shows the
space variability of rainfall.
The training method of SOCNNs is unsupervised competition learning
law. The first step is to compute a matching value between the input
patterns and the patterns that the neural nodes in the competitive
layer (i.e. the output layer) represent. Then the neural node that
has closest match to the input is identified as a winning unit. Interconnection
weights of the winning unit are updated to more closely match the
input pattern. At last after all the rainfall patterns are learned,
each set of the interconnection weights is the clustering center of
each class. All of the rainfall patterns are classified into the different
classes that the output units represent.
The space variability of rainfall in Hubei province is selected as
the case study. The observed daily precipitation data at 77 gauging
stations covering from June 20 to July 20 in 1996 during the flood
season are analyzed. According to the training algorithm of SOCNNs,
the neural nodes in input layer are 31 that are the time span of observed
data (31 days). The total learning samples are 77 that is the number
of gauging stations, i, e, each station's 31 days observed data are
selected as one rainfall pattern. All 77-rainfall patterns are input
to the network model. Through the unsupervised competition-learning
algorithm, the winning units in output layer are five. So the 77 rainfall
patterns are distributed into different five classes. The five classes
show the space distribution and variability of rainfall in Huber province.
The space analysis of rainfall is important for many problems related
to hydrological, water resources and environmental system. In this
paper, a space analysis model, SOCNNs, based on ANNs, is invested.
Its applicability in space variability analysis of rainfall is illustrated
by a case study in Hubei province.
Study on the Modelling Method of Land Water Quantity
and Quality and
Ecology Coupling System
Qiting Zuo 1 Ge Tan 2 Jun Xia 2
1. College of Water Resources and Environment, Zhengzhou University,
Zhengzhou 450002, China
2. Institute of Geographical Sciences and Natural Resources' Research,
CAS, Beijing 100101, China
Email: zuoqiting@netease.com
As the basic content of quantitative study on Managerfient of Sustainable
Water Resources, it is necessary, and difficult as well, to build
water quantity and quality and ecology coupling system model. On the
basis of application study, this paper puts forward a new method called
"Multi-Box Modeling". This method's clue is definitude,
calculation is simple, and model is reliable. It is confirmed by the
authors that the built model can stand for "land water resources
system construction connection" and can be used in quantitative
study on Management of Sustainable Water Resources.
Surface Overland Flow and its Alternation by Urbanisation.
Lev Kitaev, Elena Barabanova
Many authors, pointing out significant changes in hydrological processes
under the human activities, mean first of all those, connected with
agriculture. The Institute of Geography of Russian Academy of Sciences
is engaged in research on intcrannual changes of surface overland
flow depending on the influence of climatic and anthropogenic factors.
To the latter is referred the rising urbanisation. We can estimate
the contribution of urban territory to the surface flow of river basins.
As an example we give the results of 13-year investigations in the
upper part of the Seym basin the left tributary of the Desna river
(the steppe zone of the East European Plain). The catchments area
is 18100 km2, mcan annual discharge is 105 m3/c.
A distinguishing feature of the flow from urban territories is higher
values of the surface flow, soil and dissolved matters washout. Compared
to adjacent areas they may be 3-4, 8 and 20 times larger correspondingly.
First of all this is connected with a significant change in soil absorbing
capacity due to asphalt surfaces.
Winter period is characterised by negative trends of the surface flow
and soil washout on different types of ground surfaces, this correlates
to snow storage decrease by the beginning of spring flood due to snow
evacuation and intensive melting during thaws. As this takes place,
w4nter-spring precipitation and annual river runoff show positive
trends emphasising the importance of anthropogenic impact on natural
processes. In summer, at positive precipitation trend, surface flow
decreases slightly within municipal building areas and does not change
within villa building areas. The soil washout changes in summer in
the same way as the flow docs.
In the upper part of the Seym basin the urban territories, covering
near 5% of the total, make up a significant proportion of the net
annual volume of the surface slope flow - near 15%:
Hence significant changes in hydrological processes are observed in
a town compared to those taking place within agricultural and reserved
territories. At a relatively small city area its contribution to the
water balance of the river basins is essential.
Switching Regime Analysis for Non-linear Hydrologic
Time Series
Simon Wu1, Gordon Huang2
1.Department of Agriculture, Government of Saskatchewan, Regina, SK
S4S OBI, Canada
2.Faculty of Engineering, University of Regina, Regina, Saskatchewan,
S4S 0A2, Canada
Email: wusimon@env.uregina.ca
Time series models are valuable analytical tools for assessing potential
impacts of climate change on water resources systems. Hydrologic time
series has seen numerous applications in the past several decades.
However, most analyses have been based on the assumption that there
is a constant regime throughout the temporal dimension. In reality,
regional climate shifts have been observed around the world for many
years, which triggers changes in hydrologic behaviors of water resources.
Efforts have been made to introduce change detection methodology to
solving the problem in the application of time series in water resources
management. Change points are now normally searched and examined before
time series modeling is conducted. In addition to classical sequential
analysis, many novel methods such as Bayesian estimation and Markov
Chain Monte-Carlo simulation have been proposed to deal with change
detections in time series modeling. There have been significant amount
of literature in change-point detection methodology and their applications
in various science, engineering and business fields. However, publications
in change-point analysis for hydrologic time series have been very
few and only limited to Bayesian approaches. A common disadvantage
with the Bayesian methods is their incapability of handling nonlinear
models. Linear time series models and their corresponding change-point
detection methods basically do not support insight into switching
regimes in time series dynamics. Linear models for hydrologic forecasting
and simulation such as Auto-regressive Moving Average (ARMA) have
been dominating in research literature, but actually gained limited
acceptance in real-world practices. For example, when daily hydrologic
data are of interest, linear modes are often hard to justify. Some
innovative approaches such as neural networks, time-delay embedding,
global dynamic models, have emerged to deal with problems associated
with nonlinear time series. Non-linear time series analysis has been
applied in many hydrologic studies. However, it is relatively hard
to analyze the system dynamics due to the nonlinear nature of models,
and few studies have been found applying switching regime analysis
to nonlinear hydrologic time series forecasting or simulation.
In this paper we present an approach to detecting switching dynamics
for hydrologic time series based on Hidden Markov Model. The Hidden
Markov Model has been successfully applied to change-point analysis
in data processing in other industries like financial market and industrial
processes. A method proposed by Kohlmorgen and Lemm is adopted in
the study and applied to a typical hydrologic case with Mackey-Glass
time series. The basic theory of Hidden Markov Model is first introduced,
and followed by description of change-point analysis algorithm. The
case study with hydrologic time series is presented with discussion
focusing on the applicability of the approach to hydrologic studies.
The Hydrology Process in Mountain Vegetation Zone
in Inland River Basin in Northwest China
Kechao Song1, Ersi Kang2, Bowen Jin 1,2
1.COM and Arid Regions Environment and Engineering Research Institute,
Chinese Academy of Sciences, 260 Donggang West Road, Lanzhou 730000,
China.
2. Institute of Water Resource Conservation Forest in Qilian Mountains
of Zhangye, Gansu 734000, China
Email: songkechao@msn.com
The water resource in northwest china mainly come from mountain vegetation
zone and mountain glacier and frozen zone. In mountain vegetating
zone the main vegetation type is mountain meadow, conifer forest,
shrub wood. The main three vegetation types present in the approximate
altitude range from 1800m to 3800m, but only over a horizontal distance
a few kilometers. The average yearly precipitation in mountain is
about 400mm-500mm and about 80% of precipitation fall from may to
September.
In study, we characterize the differences of the water and heat regimes
of different vegetation stands by comparing both water and heat that
input into and output to different altitudinal vegetation stands,
then conclude that it is the special vegetation types, special ground
cover of litter moss layer, frozen layer, topography in vertical vegetation
landscape in mountain vegetation area determine the special hydrology
process in mountain vegetation zone of inland river basin. The difference
in the amount of water and heat that input in conifer forest and shrub
wood and meadow from the upper canopy is caused by the strong altitudinal
gradients of precipitation and air temperature in mountain vegetation
zone. The differences of distribution of water and heat in canopy
and soil layer are caused by the difference in the geometry structure
of canopy and the difference in the character of the soil poifle,
so the frozen depth and soil water content and the composition of
the runoff present the result that bigger runoff coefficient is presented
in higher altitude belt of mountain vegetation zone.
The interception rate of precipitation in conifer forest, shrub wood
are about 21%--35%,26%--41% respectively, if the precipitation is
larger than 3mm and less than 20mm, account for actual measurement.
Litter-moss layer in conifer forest or shrub wood reintercepts the
through fall reaching the ground surface. The litter-moss layer's
thickness is averagely 4cm-10cm, in local site can reach 15cm-25cm.
The humus layer under the litter-moss layer can accumulate to 3cm-10cm
in thickness and absorb infiltration water render the shallow soil
water content larger than the depth soil's, so there have more subsurface
runoff flow into the branch of fiver because of the larger antecedent
soil water content. About 23-34% intercepted through fall by litter-moss
layer infiltrate in shallow soil layer, about 66-87% intercepted through
fall evaporate in atmosphere account for measurement. Only in rainy
season subsurface runoff generate above seasonally frozen layer, during
winter and spring, some snowmelt and through fall storage in shallow
soil layer at the form of ice. The seasonal frozen soil layer in forest
area occur at the end of October and thaw throughout in may, during
this time, the net infiltration water all storage in shallow soil
layer and exhaust in the transpiration and subsurface runoff.
The distribution regime of precipitation that falls on meadow is controlled
by sparseness or density of grass. The infuriation water mainly used
for grass transpiration if the grass stands is density; else the rainfall
reaching to sparse grass is mainly exhausted for soil evaporation.
Generally, in grass hill slope, there have no surface runoff in process
of precipitation except in local site. In one measurement, the runoff
coefficient is only 0.04 in a continuous 34mm rainfall process. The
frozen layer in meadow area is manful for snowmelt runoff in spring,
at the starting of summer the frozen layer does not exist.
The Interval Extension Evaluation Model of Water
Environmental Quality and its Application
Jun XiaI , Baoqing Hu2
1.Institute of Geographic Science and Natural Resources Research,
Chinese Academy of Science, Beijing 100101; Wuhan University, Wuhan
430072, P. R. of China
2. School of Mathematics and statistics, Wuhan University, Wuhan 430072,
P. R. of China
Email: jxia_mail@263.net; bqhu@public.wh.hb.cn
This paper firstly introduces concepts of/E-distance, IE-locating
value and /E-correlative function and proposes interval extension
evaluation model (IEEM) and its application to water environmental
quality assessment. This method solves assessment problem while quantity
of assessed matter-element is an interval number produced by a variety
of uncertainty.
The Ratio of Transformation From Precipitation to Water Flux into
the Sea of the Yellow River, China, as Influenced by Human Activities
Jiongxin Xu
Institute of Geographical Sciences and Natural Resources Research,
Beijing 100101, China
Email: xujx@igsnrrac.cn
To quantify the transformation from precipitation to water flux into
the sea, an index of coefficient of water flux into the sea (Qw, s)
is proposed in this study, which is defined as the ratio of water
flux into the sea divided by the precipitation by volume over the
river drainage basin. It has been found that Qw, s has declined since
the 1950s, as a response of water cycle system of the Yellow River
to the changing human activities and precipitation. Due to sharp increase
in water diversion by man for irrigation, industrial and domestic
uses, a strong lateral-branch water cycle subsystem has been well
built in the Yellow River water cycle system. In the meantime, basin-wide
water and soil conservation measures have been practiced, significantly
enhancing the local water cycle from precipitation, infiltration to
evapo-transpiration.
Based on the data from 1952 to 1997, a multiple regression equation
has been established that relates Qw, s to water diversion by man,
area of land terracing and tree- and grass planting and annual precipitation.
The equation indicates that, to the decline of Qw,s, the factor in
the first place is water diversion by man, the factor in the second
is water and soil conservation measures, and precipitation is in the
third. These results may be used as reference in decision making for
the drainage basin water resources and delta environment management
of the Yellow River.
The Realization of Quasi Real-Time System of Economical
Operation of Hydropower Plant Based on Neural Network Method and Dynamic
Programming
Qiang Huang, Chenguang Xu ,Maihuan Zhao
Xi'an University of Technology, Xi'an, Shaanxi Province 710048, China
Email: mhzhao@163.com.cn
Economical operation of hydropower plant researches are mainly about
the balance of generator output, runoff and water head; the dynamic
characters and the hydrologic characteristics of turbine generator;
the reasonable distribution of load among generators; the economic
combination of generators; the start-stop schedule of generators.
Compared with short-term and long-term Economical Operation of Hydropower
Plant, the principal difficulty of the implement of Economical Operation
of Hydropower Plant (EOHP) is how to realize real-time system. In
the past the study on algorithm laid particular stress on its accuracy
while ignored its computing speed, which is essential to EOHP. For
the sake of the hydropower plant to take response in time for the
change of water level and electrical load, precise and high-speed
algorithm should be established.
Traditionally the efficiency of water turbine generator comes from
the efficiency characteristic curve of water turbine generator, which
depends on the practical test data under some typical head. Although
this method is fast enough, its error is evident. In this paper, the
technique of artificial neural network (ANN) is proposed. After the
efficiency test data under some typical head having been trained,
groups of water head and generator output of the turbine generator
are suggested as inputting structure parameters into the input layer,
the efficiencies are used as outputs. Then the proper weights and
biases are obtained, which can be used to forecast the efficiency
of water turbine generator. Practically, the water head and generator
output of last period can be used to modify the weights and biases
of ANN.
Spatial optimal operation of hydropower station, which is based on
the changing conditions of the water level and electrical load, can
be realized by dynamic programming. If the changes achieve a certain
domain, spatial optimal operation of hydropower station will begin,
else the operating way of generators in last period will be continued.
The improvements in these two respects can increase the accuracy EOHP.
And the simulation results show that they ran fast enough, which are
faster than the hardware do. Thus the quasi real-time system of economic
operation is achieved.
The Theory and Structure of SWAT Model: A Case Study
in He;he Basin
Zhonggen Wang1, Youbo Huang 2, Xianfeng Wu 3
1. Institute of Geographical Sciences and Natural Resources Research,
CAS, Beo'ing 100101, China
2. Hydraulic and Electric Engineering Department of Wuhan University,
Wuhan 430072, China
3 Institute of environmental science, Beijing Normal University, Beijing1008
75, China
Email: zhg-wang@163.net
SWAT (Soil and Water Assessment Tool) is a physically based, long-period
distributed hydrological model. It was developed to predict the impact
of land management practices on water, sediment and agricultural chemical
yields in large complex watersheds with varying soils, land use and
management conditions over long periods of time. This paper addresses
the issues of the hydrological recycle theory, the structure and functions
of SWAT model. Finally, the SWAT model is applied in the heihe (yingluo
valley) basin.
To Ascertain Design Flood of Longmenzhen Hydrologic
Station in Yi River by Using Observed Storm Data
Xianghui Yang
Hydrology Bureau; YRCC, Zhengzhou 450003, China
Email: Yangxh@371.net
Flood is usually formed by storm in the most region of China. In actual
practice, sometimes discharge-rainfall correlation method can not
be used for interpolating and extending discharge data because of
the lack of observed discharge data or the less series representative,
sometimes design flood can't be ascertained by using discharge data
because of obvious changed runoff forming conditions and breakage
of series coincidence caused by human beings activities. Design flood
need to ascertain by storm data in these cases or in the middle and
small basin without discharge data, while can add the multiformity
for calculating design flood in order to proving the rationality of
design results. Design flood results are usually ascertained by using
discharge data in Yellow River basin. In this paper, the design flood
of Longmenzhen hydrologic station in Yi River of branch Yellow River
is ascertained by using storm data. It is an attempt of the method
applying in Yellow River basin.
It is a main process for calculating design flood as follows. Firstly,
collecting 1953~ 1997 years observed discharge series and precipitation
series as calculation series, three respective big storm and flood
process in 1954,1958 and 1982 years as the typical storm and flood
process, restoring 1960~1997 years observed discharge data influenced
by Luhun reservoir regulation in Yi River upstream, and analyzing
the representative of rainfall stations. Secondly, applying Xin Anjiang
Model as runoff yield and flow concentration calculation model and
ascertaining model's parameters. The model has 4 parts including evaporation
calculation, runoff yield calculation, runoff's composition calculation
and flow concentration calculation, with 14 parameters. Thirdly, according
to 1953~ 1997 years average area rainfall, the maximal l day, 3days,
5days, 12days design area rainfall Xp(P=0.01%, P=0.1%, P=l%) are calculated
by using P-III frequency distribution curve, then the design rainfall
process corresponding to 3 typical storm process could be ascertained
by the homogeneous frequency enlargement. Then, we could calculate
the design flood process by the design rainfall process using the
runoff yield and flow concentration model with its parameters and
initial conditions. Fourthly, to ascertain Longmenzh's design flood
volume by discharge data and compare with the results of design flood
volume by storm data.
The calculation results express that there are not obvious difference
between the design flood volume calculated by storm data and by discharge
data with Xin Anjiang Model, its parameters and initial conditions.
Therefore, it is thought that the method of ascertaining design flood
by storm data would be possible, could be applied to the middle or
small basin lacking discharge data.
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