Pengaruh Tutupan Lahan terhadap Base Flow Index DAS Way Seputih Provinsi Lampung

Tujuan penelitian ini adalah menganalisis nilai Base Flow Index (BFI) dan debit baseflow DAS Way Seputih; menganalisis nilai Curve Number (CN) composite DAS Way Seputih tahun 2005, 2009, dan 2011; serta menganalisis pengaruh perubahan tutupan lahan terhadap baseflow DAS Way Seputih. Penentuan baseflow tahun 1973-2006 menggunakan Metode RDF (Recursive Digital Filter) terbaik berdasarkan uji kinerja, yaitu Root Mean Square Error (RMSE), R2, dan grafik FDC (Flow Duration Curv) di antara metode Lyne&Hollick, EWMA, Chapman Algorithm, dan Nathan and McMahon. Kemudian Metode RDF terbaik ini dibandingkan dengan Model SCS-CN (Soil Conservation Sevice Curv Number) untuk menentukan baseflow dan BFI tahun 2005, 2009, dan 2011 berdasarkan uji kinerja. BFI DAS Way Seputih tahun 2005, 2009, dan 2011 berturut-turut adalah 0,8178; 0,54225; dan 0,649502. Untuk nilai CN I composite, CN II composite, dan CN III composite tahun 2005 berturut-turut adalah 63,9191; 79,8869; dan 80,1315. Nilai CN I composite, CN II composite, dan CN III composite tahun 2009 berturut-turut adalah 42,7834; 60,8427; dan 83,6676. Sedangkan Nilai CN I composite, CN II composite, dan CN III composite tahun 2011 berturut-turut adalah 66,4066; 81,9460; dan 94,5943. Nilai BFI dipengaruhi oleh debit baseflow dan debit sungai. Debit sungai dipengaruhi oleh curah hujan, sedangkan debit baseflow dipengaruhi oleh perubahan luas tiap jenis tutupan lahan.

Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method?

The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance (CMB) method are two widely used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a “false” calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-conductivity water flushed from swamps and depressions by rainfall, but not low-conductivity interflow and bank storage return flow. This difference results in obvious peak misalignment and periodic deviation between the baseflow sequences obtained by the two methods, thereby preventing calibration. However, multi-component separation of streamflow can be achieved through comparison. Future research should recognize the deviations between the separation results obtained by the different methods, identify the reasons for these differences, and explore the hydrological information contained therein.

Multifarious methods of baseflow estimation for typical catchments in the Yellow River Basin, China

Baseflow is crucial to maintaining river flow during low rainfall periods. The baseflow estimation is important to water supply and ecological environmental protection in the Yellow River Basin (YRB), China. This paper comprehensively assessed the applicability of four single-parameter digital filtering, recursive digital filtering, and HYSEP (Streamflow Hydrograph Separation) methods across four typical catchments in the Yellow River Basin: Zuli River Basin, Kuye River Basin, Tuwei River Basin, and Jingle sub-basin. We also investigated annual and monthly variations in baseflow. We found the standard deviation and coefficient of variation of baseflow index through recursive digital filter were relatively small. And the baseflow process line was smoother and more reasonable in typical year and typical storm-flood events, which conformed to the damping and hysteresis effect of underlying surface. Thus the recursive digital filter method had the best performance, which was recommended for baseflow separation in the YRB. The estimated baseflow index of typical basins were between 0.354 and 0.502. In addition, inter-annual baseflow showed a decreasing trend and intra-annual baseflow was characterized by uneven distribution, which was subject to the characteristics of each basin. As baseflow is important for the YRB, suitable assessment of baseflow is crucial to efficient management of water resource.

Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method?

The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance method (CMB) are two widely-used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method, and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a false calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The reason for this phenomenon is that the baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-salinity water flushed from swamps and depressions by rainfall, but not low-salinity interflow and bank storage return flow. Future studies can realize the multi-component separation of streamflow or identify the contribution of different transient water sources to streamflow by comparing the results of these two methods.

Hybrid Approach to Design of Two Dimensional Stable IIR Digital Filter

In this paper, the magnitude optimization for the design of two dimensional digital filter is attempted and new design method for a two-dimensional (2-D) recursive digital filter is proposed via appropriate genetical swarm optimization with the introduction of the desired stability constraints. The method is tested on a numerical example and the obtained results are presented with previously published methods.

Assessment of variation of baseflow contribution to stream flow in a hard-rock aquifer

<p>Stream flow is combination of two major portion of flows as direct runoff and baseflow. Study of baseflow and direct runoff is much needed to understand the hydrology of a watershed, including surface and sub-surface water interaction, and to assess the ecological functioning of streams. Tropical countries like India facing major challenges in water management; especially for irrigation and drinking water. In such regions identification of baseflow sources, knowledge of baseflow availability and analysis of their varied contribution to the stream is needful. Baseflow plays a critical role in maintaining streamflow, especially during pre and post monsoon periods.</p><p>Recursive digital filter technique is adopted for the daily stream flow data measured at river gauge stations on Kabini stream of Cauvery basin, to separate baseflow component from stream flow hydrograph. In terms of hydrogeology, since Cauvery basin occupied with hard-rock terrain, it is important to investigate the intra annual variation of groundwater discharge into the stream. In the present study an attempt has been made by considering daily stream flow data at two river gauge observation points, and annual baseflow and baseflow index is calculated through RDF method. The results obtained from RDF method are validated with the help of hydrogeochemical tracers by applying End Member Mixing Analysis (EMMA) to the hydrogeochemical data for the period of 2018-19 hydrological cycle.</p>