Reliability of spring recession curve analysis as a function of the temporal resolution of the monitoring dataset

Mountain springs represent one of the largest and most precious sources of potable water in Italy, necessary to meet the water needs of the population. Optimizing the present and future management strategies of mountain groundwater resources has become increasingly necessary. The accuracy and frequency of the flow rate (Q) measurements determine and restrict the processes that can be studied using spring hydrograph and recession curve analysis. Therefore, to properly define mountain aquifers’ hydrogeological properties, it turns out important to highlight the variation of the error in the estimation of the hydrogeological parameters as the time interval of sampling varies. In this paper, recession curve analysis was performed on two different mountain springs (Spring 1 and Spring 2) of north-western Italy, firstly considering available 4-h resolution measuring data and subsequently by resampling data to simulate longer sampling intervals of 1, 3, 7, 15, and 30 days.The resulting distribution of errors introduced by longer acquisition intervals underlined how the percentage error increases with increasing acquisition interval. For obtaining an adequate estimation of mountain aquifer hydrodynamic parameters, in place of continuous hourly data, 1-day and 3-day sampling intervals with associated errors respectively lower than 5% and 10% were found to be valid.

Multiple measures of water storage in monsoon Asia

<p>Temporal water storage is a fundamental component of the terrestrial water cycle. Almost all precipitation falling on land is transferred via a series of short- to long-term storage locations, e.g. groundwater, to rivers, and eventually ends in the oceans or, through evapotranspiration, back in the atmosphere. The intermediate storage compartments are recharged during precipitation events and subsequently purge during phases of very little precipitation input. Methods to estimate water storage variations are often limited to specific, well-monitored locations and the findings from there are often difficult to generalize or to upscale. At the same time large scale monitoring represents an average of the entire system with very little prediction power for small areas. Thus, measures of storage from small systems can be difficult to compare to large systems and vice versa. In this recently published study (Schmidt et al., 2020) we compare three independent methods of estimating water storage variations for systems spanning over three orders of magnitude in basin area: 1) GRACE, 2) hydrograph recession curve analysis, and 3) quantifying precipitation-discharge hysteresis loops. We measured storage using all three methods for 242 watersheds in Asia spanning a size range from 10<sup>3</sup> to 10<sup>6</sup> km<sup>2</sup> and find that GRACE- derived storage correlates well with the quantification of hysteresis terms but recession curve derived dynamic storage does not correlate with hysteresis terms or GRACE-derived storage. Thus, we argue that precipitation-discharge hysteresis may be able to be scaled to GRACE-derived storage as an  independent estimate of storage to systems much smaller than the typical resolution of GRACE. Hysteresis-derived storage correlates well with mean monsoon rainfall in the upstream watershed while recession-derived dynamic storage does not. This suggests that hysteresis- and GRACE-derived storage may be input limited. In contrast, recession-derived dynamic storage does not correlate with topographic, climatic, or land cover metrics, suggesting that it may be limited by the rate at which water infiltrates into deep groundwater and then enters the river system. In addition, we find that recession-derived dynamic storage is a factor of seven lower than hysteresis-derived or GRACE derived storage. Recession-derived dynamic storage represents the annual variability in deep and saturated groundwater storage, a “leaky bucket” that is recharged from the top and “leaks” into rivers from deeper storage. The GRACE and hysteresis derived storage in turn integrates groundwater variations in addition to other storage units at or close to the Earth surface, such as snowpack, lakes, and soil moisture. These data may be able to be used to better quantify storage terms in hydrologic modeling and might help to improve GRACE data products.</p> <p>Schmidt, A. H., Lüdtke, S., & Andermann, C. (2020). Multiple measures of monsoon-controlled water storage in Asia. Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2020.116415</p>

Characterizing River Baseflow Recession Using Linear Reservoir Model in Alang Watershed, Central Java, Indonesia

Alang is a sub-watershed emptying into the Gajah Mungkur Reservoir in Wonogiri, Central Java Indonesia, with an area of 51.01 km2 and lithology composed of Baturetno Formation and Wonosari Formation. Baseflow is a major component of river flow during the dry season. Hence, the characterization of its recession becomes necessary, and it can be performed with innovation in baseflow hydrological modeling, that is, the recession curve. This study was designed to describe the distinctive features of baseflow recession using a linear reservoir model, which is depicted in individual and master recession curves. The baseflow recession in AlangSubwatershed was represented by a combination of varying initial recession discharge (Q0), α, and recession constants (Krb). The individual recession curves were typified by Q0=0.19-9.11, α= 0.089-0.243, and Krb=0.7843-0.9148. As for the master recession curve, it had Q0=9.99, α=0.085, and Krb=0.928. These results signify a sloping recession curve, meaning that the water storage and aquifer characteristics that store and transmit water in Alang Subwatershed are in good condition.

The influence of geomorphological and lithological diversity in catchment hydrodynamic behavior. The case of Arunca river catchment, Portugal

<p>The catchment hydrologic behavior is the result of a complex interaction between its physical characteristics, such as bedrock lithology, superficial geology, soil type and depth, vegetation type, topography, and drainage network. It has been known for a long time that, in addition to climate characteristics, the variations in the geomorphological and lithological features inside the basin originate specifics surface hydrodynamics, particularly in terms of runoff velocity, runoff amount and lag time. Understanding the hydrological functioning of the different sectors in a basin is essential to its spatial planning and management under the present scenario of climate uncertainty.</p><p>The Arunca river catchment is situated in the center-west of Portugal and occupies an area of about 550 km<sup>2</sup>. One of the main characteristics is its geomorphological and lithological diversity, which is responsible for the existence of two different hydrological dynamics: (i) a karstic hydrodynamic where the cryptoreic drainage is absolutely dominant, and (ii) a fluvial hydrodynamic, characterized totally by surface runoff (exorheic drainage). The overall aim of this empirical study is to investigate and quantify the geomorphological and lithological influence on the hydrological behavior of these areas, which present very different physical characteristics.</p><p>Methodologically, we have adopted an empirical approach based on the analysis of spring and river hydrographs for simultaneous hydrometeorological events. Daily and hourly datasets of rainfall and spring and river flow were performed from 2009/2010 to 2014/2015. The data of the outflow from the karst area were collected by a gauge station at the main spring of the Degracias-Sicó karst aquifer. A second gauge station registered the data of river flow at the Arunca river sub-catchment, a non-karstic area, where only surface hydrodynamic is observed. Both gauge stations recorded data with an acquisition time interval of 20 minutes. The rainfall data were registered every 0.2 mm by two rain gauges installed, one in each studied sector of the catchment. An intra-annual period of analysis was established from October to May in order to understand the hydrodynamic functioning under diverse underground hydraulic conditions in different moments along the hydrological year. For every hydrometeorological event in both study areas of the basin, the hydrograph analysis focused on the calculation of the lag time, the time lag between the hydrological response of spring and river. The shape of the rising limb and the recession curve also was examined.</p><p>The results display a similar reaction of both sectors to a rainfall event. However, the lag time is shorter in the river than in spring, and the hydrograph of the river presents a more pronounced peak flow.  The main difference stands in the recession curve, particularly in the falling limb, much steeper in the river hydrograph, which shows the return to pre-event conditions only some hours after the peak flow. Basing on the simple analysis of the hydrograph, it is clear the effects of geomorphology and lithology in catchment hydrodynamic behavior.</p>

Analisis MRC untuk Karakterisasi Akuifer Karst di Mataair Mudal, Kabupaten Kuloprogo

Akuifer karst memiliki triple porosity yang membuat karakterisasinya sulit dilakukan. Tujuan dari penelitian ini adalah menganalisis komponen hidrograf banjir dan membuat Master Recession Curve (MRC) pada akuifer karst yang mengimbuh Mataair Mudal. Data yang digunakan adalah debit aliran dan curah hujan yang tercatat setiap 30 menit pada November 2017 hingga Mei 2018 (6 bulan). Hasil penelitian menunjukkan bahwa Mataair Mudal memiliki complex discharge regime dengan derajat karstifikasi pada kelas 5,5. Analisis komponen hidrograf banjir menguatkan hasil perhitungan derajat karstifikasi. Waktu menuju puncak banjir (Tlag) yang tergolong cepat (2,5 jam) menunjukkan telah adanya aliran conduit. Perhitungan waktu menuju aliran dasar (Tb) baik secara manual (hidrograf banjir) maupun automatis (MRC) memiliki rerata sekitar 40 jam yang mencerminkan bahwa akuifer karst yang mengimbunya masih baik dalam menyimpan airtanah. Secara keseluruhan, akuifer karst di Mataair Mudal masih didominasi oleh retakan bertipe diffuse, meskipun sudah memiliki retakan bertipe conduit yang cukup berkembangThe objective of this research was to analyze the nature of the flood hydrograph components and create a Master Recession Curve (MRC) to estimate the degree of karstification in Mudal Spring. Discharge and rainfall data were recorded every 30 minutes at time intervals between November 2017 and May 2018. The results show that Mudal Spring has a complex discharge regime with a karstification degree in the class of 5.5. Meanwhile, the time to peak flood (Tlag) which is relatively fast (2.5 hours) shows the existence of conduit flow in the flood event. Calculation of time to baseflow (Tb) has an average of 40 hours which reflects that the karst aquifer was still good in storing groundwater. Overall, karst aquifers in Mudal Spring are still dominated by diffuse type voids, although they already have conduit type voids that are quite developed.

Master Recession Curve (MRC) analysis to characterize karst aquifers of several springs in the north side of the Karangbolong (Gombong) karst area

Karst aquifers have triple porosity (diffuse, fissure, and conduit) which makes their characterization difficult, and often requires a combination of particular methods and investigation over a long period. The purpose of this study is to analyse the components of the flood hydrograph and create a master recession curve (MRC) in karst aquifers that recharge several springs on the north side of the Karangbolong Karst Area (Gombong). The springs studied include Kalisirah, Jumbleng, and Kalikarak springs. The data used are time-series discharges recorded every 15 minutes from November 2018 to March 2020. Furthermore, the reconstruction of the flow regime for MRC is carried out with the help of RC 4.0 software, which is at the same time able to define the level of karst aquifer development. The results showed that Kalisirah and Kalikarak Springs have a complex discharge regime with a degree of karstification in class 8, while Jumbleng Springs in class 5. Analysis of the components of the flood hydrograph reinforces the results of the calculation of the karstification degree. The time to the peak (Tlag) of the Kalisirah and Kalikarak Springs is relatively fast (1.94 and 1.44 hours), which indicates that conduit flow has developed, while Jumbleng spring has a longer Tlag of 2.69 hours. Calculation of time to base flow (Tb) both manually (by flood events analysis) and automatically (by MRC) shows that Kalikarak Springs has the longest time with an average of about 31 hours which reflects that karst aquifers which contribute to it are still quite good in storing groundwater, while Jumbleng spring has the fastest Tb value with an average of 17.25 hours which reflects the shortest release of water storage compared to the other two springs.