Morphometric Characterization And Hydrological Modelling Of Karst Watershed Using SWAT Model

Karst is a terrain that evolves from the dissolution of carbonate rock coming into contact with acidic meteoric water.This landscape is generally found to be between 7-12%of the continental surface of earth,where over 25%of the world's population depend on karst aquifers.Yet,few studies have be conducted on the application of computing technology whether in the field of geographic information systems or finite element modelling to karst water resources.This may be attributed to the inherent complexity of karst geology which makes modelling the multiple porosity matrix of its aquifers difficult.Another associated problem is that karst terrains are poorly understood and generally treated as other sedimentary formations.This has led to several environmental and infrastructural damage as well as huge financial losses.Despite these challenges,some successes have been recorded,especially in the last decade.However,no standardized study on how to carry out hydrological modelling in karst environments exists yet.Also,karst environments require special treatment for their underlying heterogeneity and susceptibility to environmental risks.It is towards these needs that this research is carried out with an aim of improving our understanding of watershed processes and sustainable water resources management in karst environments.In this work,we outline some important research questions and set to answer them systematically with aim of developing a standardized approach for modelling watershed processes in karstified basins.These questions are;(i)how do karst watersheds differ from non-karst watersheds?(ii)What are the effects of karst features on watershed drainage system?(iii)What is the volumetric contribution of major karst features in a watershed on streamflow and how do these features affect groundwater quantity and quality?(iv)Can rainfall-runoff be modelled in karstified environments using the unmodified Soil and Water Assessment Tool(SWAT)?Two neighbouring watershed in Gaolan River basin were selected as case studies.The first,Miaogou which is a highly karstified watershed and is the main focus of our work.The second,Gaojiaping,a non karst watershed of mainly igneous and metamorphic rocks,is used to elucidate and contrast between a typical karst watershed and a non karst watershed.These differences are related to mainly topographic,hydrologic and geomorphic characteristics.Firstly,in chapter two,a morphometric characterization of the watersheds was conducted in order to provide us with a sound conceptual understanding of the watershed physical properties and how they may influence hydrological process.This is imperative because it provides valuable information necessary before embarking on modelling.GIS and remote sensing data and techniques were used to derive morphometric parameters of Miaogou karst watershed and Gaojiaping watersheds.Results showed that the topography of Miaogou is defined by complex relief due to denudation of carbonate rock matrix(limestone and dolostone).Also,Miaogou has very high concavity index which leads to high runoff during precipitation events.In addition,hydrographic computations showed the watershed area to be 45km~2,with its main stream channel to be about 15km long while total length of drainage is 30.86km while Gravelius index was calculated to be 1.93.Furthermore,geomorphic results indicated that the karst in Miaogou is a variant of the Fengcong cone karst having conical geometry with long and wide depressions which were delineated and totalled four in number.There are also four caves and eighteen sinkholes in the area where one acts as an active hydrologic conduit to one major spring(BLQ).On the other hand,Gaojiaping watershed had no karst features and is representative of a typical equal porous media with homogeneous crystalline formation.Secondly,in chapter three,fifteen(15)storms were selected from the streamflow hydrograph of Miaogou(karst)and Gaojiaping(Non-karst)watersheds to conduct a hydrograph recession analysis and streamflow component separation.The objectives were to determine the effects of karst features on watershed drainage system as well as estimate the volumetric contribution these features on total streamflow.Also,we further examined their consequence on groundwater quantity and quality in Miaogou watershed.Thus,using the exponential method for recession curve analysis,four major segments of the recession limb of each storm were selected to calculate their respective recession coefficient.These recession coefficients were then extended to characterize the streamflow components with a view to evaluate the volume,percentage and characteristic of each streamflow contribution.The results show that the karst watershed in contrast to the non-karst watershed tended to drain larger of volumes precipitation through it's their aquifer matrix due to extreme heterogeneity as characterized by huge caves and fractures.While other karst features such as sinks and closed depression acted as siphoning conduits that transmit runoff more rapidly through large underground cavities to larger springs and then smaller ones which contribute to total streamflow at the basin outlet.These common karst features found in highly karstified watersheds are referred to in this study as karst drainage areas(KDA)which generate what we has also been termed in this study,karst drainage flow(KDF).The KDF is represented by the second stage of the recession limb and shares similar properties as overland flow due to its high recession coefficient.The statistically significant variance in recession coefficients as established by analysis if variance(ANOVA)between the two watersheds highlight the strong impact of the KDA on aquifer specific yield over time.Although during dry periods,represented by the fourth recession stage,the recession coefficients for both watersheds do not have as much statistical variance as the first two recession stages,indicating that the micro fissures and pores that control much of the delayed discharge is nearly similar in character and not as significantly different.This fact provides valuable information for groundwater resources availability.Furthermore,since higher recession coefficient index for successive recession stages imply high sensitivity to groundwater pollution as well as poor aquifer specific yield over time,the environmental implication must be emphasized.Groundwater pollution is a major problem especially in areas where it remains the primary sources of fresh water as in our case areas.Previous groundwater vulnerability studies established that Maiogou area has a high intrinsic susceptibility to pollution.The recession coefficients calculated in this study further elaborate on the severity of the aquifer sensitivity to pollution.Therefore stronger water management practices must be enforced.Finally,in chapter four,the SWAT model was used to model the two watershed areas for monthly streamflow prediction.Model results showed a close correspondence with initial analytical solutions and GIS based mapping.In addition,twelve critical parameters were selected for calibration of the models for a period of two years.For Miaogou watershed the most sensitive parameters were found to be the HRU_SLP and CN2 which we attributed to the topographical factors and basin shape.However,in reality this is due to the KDF which is generated by the KDA.In Gaojiaping,the SHALLST and OV_N parameters were found to be the most sensitive perhaps due to sinuosity of the stream channels as well as higher baseflow volume.After validation of the model,the objective solutions R~2 and NSE were found to be 0.6 and 0.6 respectively for the year 2015 while for the year 2016 they were found to be 0.7 and 0.6 respectively.This shows a strong fit in both magnitude and hydrodynamics between the predicted streamflow values and observed values.As for the non karstified watershed,model efficiency R~2 and NSE were found to be 0.73 and 0.1 respectively for the year 2016.This implies strong fit for the hydrodynamics but not for the magnitude.Overall,the unmodified SWAT model was found to be promising but requires sound understanding of the watershed processes as well as long term data.The significance of this research work include the following;(i)comparative assessment of water drainage characteristics of karst and non-karst basins;(ii)determining the water volume drained by karst areas from the watershed,which is termed in this study as Karst Drainage Flow(KDF);(iii)elucidating the influences of well-developed karst geology on spatial and temporal distribution of karst water resources;(iv)proposing a standardized protocol for runoff modelling in karst watersheds using unmodified Soil and Water Assessment Tool(SWAT);(iv)pioneering a comparative hydrologic modelling of a karst and non karst watershed;(v)discovering the potential groundwater shortage and pollution risk for Xingshan County in Miaogou catchment.Moving forward,studies in machine learning may proffer an approach to monitoring stream discharge over longer periods with the aim of mastering the hydrograph trend for every unique storm.With longer observational data,the recession coefficient of the karst drainage flow for entire hydrologic year can be determined and hence provide an accurate means to calculate the karst drainage factor,that is,the rate at which the watershed drains any given storm primarily from the influence of karst areas.In the future,this will prove valuable in groundwater resources estimation,evaluation and modelling.