The Effects of Exchange Flow on the Karst Spring Hydrograph under the Different Flow Regimes: A Synthetic Modeling Approach

In this study, a synthetic modeling approach is proposed to quantify the effect of the amount and direction of the exchange flow on the karstic spring discharge fluctuations under different hydrologic conditions corresponding to high and low flow conditions. We hypothesis that the spring discharge fluctuations constitute a valuable proxy to understand the internal processes of the karst system. An ensemble of spring hydrographs was synthetically produced to highlight the effect of exchange flow by exploring the plausible range of variability of coefficients of exchange flow, conduit diameter, and matrix hydraulic conductivity. Moreover, the change of the rate of point recharge through the karst conduit allows for the quantifying of the sensibility of the spring hydrograph to the directions of exchange flow. We show that increasing the point recharge lies to a remarkable linear recession coefficient (β) as an indication of the conduit flow regime. However, a reduction in and/or lack of the point recharge caused the recession coefficient to change to exponential (α) due to the dominant effect of the matrix restrained flow regime and/or conduit-influenced flow regime. The simulations highlight that the exchange flow process from the conduit to the matrix occurred in a short period and over a restricted part of the conduit flow regime (CFR). Conversely, the exchange flow dumped from the matrix to the conduit occurs as a long-term process. A conceptual model is introduced to compare spring hydrographs’ characteristics (i.e., the peak discharge, the volume of baseflow, and the slope of the recession curve) under the various flow conditions with the directions of the exchange flow between the conduit and the matrix.

Impacts of Artificial Regulation on Karst Spring Hydrograph in Northern China: Laboratory Study and Numerical Simulations

Karst aquifers produce the world’s largest springs and supply the water resources to about a quarter of the global population while being influenced by high-intensity human activities. Knowledge about spring discharge hydrographs driven by the effects of artificial regulation is essential to develop practical strategies for the management of karst groundwater. Based on hydrogeological conditions of the karst aquifer in Jinan, a two-dimensional laboratory tank was constructed, and a corresponding numerical simulation model was developed to explore how artificial regulation drives spring hydrographs in northern China. The results showed that the spring hydrographs were significantly changed under the effects of artificial regulation. The recession coefficient increased with pumping and decreased with increasing injection rates. The late sub-recession of spring discharge did not obey the exponential recession under the influence of injection. Pumping and injection in conduit zones showed more obvious effects on the recession coefficient in the late sub-recession curves. Groundwater exchange between conduits and fissure zones differed totally for different artificial regulation modes. With continuing rainfall, the flow fields were gradually controlled by rainfall. There was a time lag in the flow fields caused by rainfall. Under the stress of exploitation at different positions, stagnation points appeared at different locations in fissure zones, and locations of stagnation points were highly dependent on the positions of pumping wells. These findings are essential for better management of karst groundwater and karst spring protection.

Watershed Characterization and Hydrograph Recession Analysis: A Comparative Look at a Karst vs. Non-Karst Watershed and Implications for Groundwater Resources in Gaolan River Basin, Southern China

Karst watersheds are often treated as non-karst watersheds that can lead to several hazards. Hence, how do karst watersheds differ from non-karst watersheds and what are the effects of karstification on groundwater availability and quality? In this study, we contrast between a karst and non-karst watershed by elucidating their geomorphological peculiarities and potential impact on spatio-temporal availability and quality of groundwater. GIS morphometric mapping and hydrograph recession analysis are applied to map the watershed features and estimate hydrograph recession coefficient to define the groundwater drainage characteristics as well as the influence of karst drainage attributes (KDA). Furthermore, we characterize streamflow components based on the hydrograph recession limbs (segments) and infer their contributing geomorphological factors. Results show that the karst watershed has higher recession coefficients for successive recession limbs. Consequently, it drains larger volumes of groundwater primarily due to the KDAs, which transmit interflow and groundwater flow more rapidly through large cavities to springs as well as stream channels. The KDAs generate what we term karst drainage flow (KDF), defined by the second recession limb which has high recession coefficient as the first limb (overland flow) and strongly contrasts with the non-karst watershed from visual and ANOVA analysis. The effect is that karst aquifer yield over time is significantly lower and highly exposed to pollution compared to the non-karst aquifer. Consequently, sustainable water management practices should be adopted to ensure the availability and safety of groundwater reserves.

OPERATIONAL MECHANISM OF KARST SPRING “LOGARAS”, NEAR THE VILLAGE “SKORTSINOU”, ARCADIA, (PELOPONNESUS)

This paper presents information on the behavior of the Logaras karst spring, which is located 2.5 km north of Skortsinou village of the Municipality of Falaesia. This spring discharges the water table hosted in the carbonate rocks located in the area among Skortsinou, Petrina, Soulario and Voutsaras Villages. This area consists of thin-platy limestones of Pindos Unit that overlay the “First Flysch” formation, which is the stratigraphic bedrock of the aforementioned limestones. Aiming at the accurate determination of the boundaries of the spring’s hydrological basin, the geological map of I.G.M.E., sheet “Megalopolis” (Papadopoulos 1997 και Luettig & Vingen 1964) was re-examined. The geological and tectonic observations that derived from this process contributed to the analysis of the spring’s mechanical operation. This led to the conclusion Logaras Spring is a contact spring. Furthermore, discharge measurements of the spring took place for the period from 24/6/2006 to 26/10/2007 and the relevant hydrograph was drawn, from which the recession coefficient was calculated. More particularly, the spring’s recession coefficient for the hydrological years 2005 – 2006 and 2006 – 2007 is 1,9·10-3 and 4,3·10-3 respectively, while the dynamic volume reach 5,4 • 106 m3 and 1,7 • 106 m3 respectively.

HUBUNGAN ANTARA INDEKS VEGETASI NDVI (NORMALIZED DIFFERENCE VEGETATION INDEX) DAN KOEFISIEN RESESI BASEFLOW PADA BEBERAPA SUBDAS PROPINSI JAWA TENGAH DAN DAERAH ISTIMEWA YOGYAKARTA

The background of this research is the decrease of environment capacity in cacthment ecosystem, especially impact of vegetation forest on behavior streamflow. The indicators of cacthment destruction can be seen through hydrograph characteristics. Evaluation of cactment respons of flow hydrographic as an evaluation tools of river catchment responses becomes very important to analyze because it is a benchmark in determination several policy about flood, drough, sedimentation and landslide handling. The research purpose is to analyze the relationship between vegetation index NDVI (Normalized Difference Vegetation Index) and the characteristic of baseflow recession coefficient at several subcatchment areas in province of Central Java and Specific District of Yogjakarta.The method of this research is surveillance on data recording of AWLR (Automatic Water Level Recorder) and data of River Flow Measuring Stations in order to separate the baseflow by calibration curve, and image interpretation of Landsat ETM+ for the transformation of vegetation index (NDVI-Normalized Difference Vegetation Index).The analysis on recession coefficient data (Krb) and NDVI were correlated to analyze the strength of relationship between these two parameters. The results of statistical analysis on index NDVI and recession coefficient showsthat NDVI and recession coefficient value at R2 is 0.1427, F = 2.17 which is not significant at 1% significance level of 0.1646. The result shows a very weak correlation of 0.077 which mean that vegetation density (NDVI index)has a very weak control on low flows. Basically, river baseflow is a genetic component of river flow which comes from aquifer storage and/or other low flow sources. Thus, geology and soil have a significant effect on baseflow.

Accuracy of Snowmelt Runoff Simulation

Results of runoff simulations from various basins using a snowmelt runoff model were analyzed in order to predict the accuracy of simulations in future applications of the model. It was found that the model can be applied to nearly any mountainous basin where snowmelt runoff is an important factor if input data on temperature, precipitation, and snow cover are available. The simulation accuracy will depend on the quality of the input data as well as on the density of observations, size of the basin, care in determination of the recession coefficient, and amount of precipitation during snowmelt. Most accurate simulations will result when: 1) temperature and precipitation are recorded at the basin mean elevation; 2) snow cover observations are available once per week; 3) several climatic stations are available for large basins; and 4) a few years of runoff records exist for determination of the recession coefficient. Decreases in simulation accuracy will be expected as these optimum conditions are compromised, however, acceptable simulations will result with the following minimum conditions: 1) temperature and precipitation data are available in the general vicinity of the basin; and 2) snow cover observations are available 2-3 times during the snowmelt season. The availability of satellite observations of snow cover extent has permitted successful application of the model to large basins.