The Radius of Influence Myth

Empirical formulas to estimate the radius of influence, such as the Sichardt formula, occasionally appear in studies assessing the environmental impact of groundwater extractions. As they are inconsistent with fundamental hydrogeological principles, the term “radius of influence myth” is used by analogy with the water budget myth. Alternative formulations based on the well-known de Glee and Theis equations are presented, and the contested formula that estimates the radius of influence by balancing pumping and infiltration rate is derived from an asymptotic solution of an analytical model developed by Ernst in 1971. The transient state solution of this model is developed applying the Laplace transform, and it is verified against the finite-difference solution. Examining drawdown and total storage change reveals the relations between the presented one-dimensional radial flow solutions. The assumptions underlying these solutions are discussed in detail to show their limitations and to refute misunderstandings about their applicability. The discussed analytical models and the formulas derived from it to estimate the radius of influence cannot be regarded as substitutes for advanced modeling, although they offer valuable insights on relevant parameter combinations.

Dynamics of Tree outside Forest Land Cover Development and Ecosystem Carbon Storage Change in Eastern Coastal Zone, Bangladesh

Tree outside forest (TOF) has immense potential in economic and environmental development by increasing the amount of tree vegetation in and around rural settlements. It is an important source of carbon stocks and a critical option for climate change regulation, especially in land-scarce, densely populated developing countries such as Bangladesh. Spatio-temporal changes of TOF in the eastern coastal zone of Bangladesh were analyzed and mapped over 1988–2018, using Landsat land use land cover (LULC) maps and associated ecosystem carbon storage change by linking the InVEST carbon model. Landsat TM and OLI-TIRS data were classified through the Maximum Likelihood Classifier (MLC) algorithm using Semi-Automated Classification (SAC). In the InVEST model, aboveground, belowground, dead organic matter, and soil carbon densities of different LULC types were used. The findings revealed that the studied landscapes have differential features and changing trends in LULC where TOF, mangrove forest, built-up land, and salt-aquaculture land have increased due to the loss of agricultural land, mudflats, water bodies, and hill vegetation. Among different land biomes, TOF experienced the largest increase (1453.9 km2), and it also increased carbon storage by 9.01 Tg C. However, agricultural land and hill vegetation decreased rapidly by 1285.8 km2 and 365.7 km2 and reduced carbon storage by 3.09 Tg C and 4.89 Tg C, respectively. The total regional carbon storage increased by 1.27 Tg C during 1988–2018. In addition to anthropogenic drivers, land erosion and accretion were observed to significantly alter LULC and regional carbon storage, necessitating effective river channel and coastal embankment management to minimize food and environmental security tradeoff in the studied landscape.

A Multi-decadal Analysis of Reservoir Storage Change in Developing Regions

The limited amount of shared reservoir monitoring data around the world is insufficient to quantify the dynamic nature of reservoir operation with conventional ground-based methods. With the emergence of the Reservoir Assessment Tool (RAT) driven by a multitude of earth observing satellites and models, historical observation of reservoir operation spanning 35 years was made using open-source techniques. Trends in reservoir storage change were compared with trends of four critical hydrologic variables (precipitation, runoff, evaporation, and Palmer Drought Severity Index) to understand the potential role of natural drivers in altering reservoir operating pattern. It was found that the reservoirs in Africa were losing active storage at a rate of more than 1% per year of total storage capacity. Smaller reservoirs (with a capacity of less than 0.5 km3) in South-East Asia were found to experience a sharp gain in storage of 0.5% to 1% per year of total storage capacity. Storage change trends of large reservoirs with multiple years of residence time that are designed for strategic water supply needs and drought control were found to be less affected by precipitation trends and influenced more by drought and evaporation trends. Over Africa, most reservoir storage change trends were dictated by evaporation trends, while South Asian reservoirs appear to have their storage change influenced by drought and evaporation trends. Finally, findings suggest that operation of newer reservoirs are more sensitive to long-term hydrological trends and the regulated surface water variability that is controlled by older dams in the upstream.

GROUNDWATER MONITORING USING GRACE MISSION

Since last few decades, India has met to major crises related to groundwater. Major cities, for example, Delhi, Chennai, Bengaluru etc. are facing extreme risk of water crisis. In next few decades, this may lead to a major water crisis when this non-renewable resource is exhausted. Gravity Recovery and Climate Experiment (GRACE) mission, widely used for monitoring of groundwater storage change, could be utilized to get the information of exact amount of water above or below the surface of the earth that may be used to counter act over such situation of water crisis. GRACE mission consists of two earth orbiting satellite vehicles (SVs) separated by 220 km with the objective of computing change in gravity by increasing or decreasing distance between both the SVs caused by higher or lower gravity masses. The primary objective of the presented work is to obtain the liquid water equivalent height in a selected area using GRACE mission data with GLDAS soil moisture data. The advantage of using GRACE is that it provides better accuracy (fraction of 1cm) in comparison to traditional methods, therefore, larger extent could be covered. This paper extensively discusses about GRACE application (especially groundwater monitoring), challenges with GRACE missions and about effective methods for groundwater recharge.

Adaptive Determination of the Flow Accumulation Threshold for Extracting Drainage Networks from DEMs

Selecting the flow accumulation threshold (FAT) plays a central role in extracting drainage networks from Digital Elevation Models (DEMs). This work presents the MR-AP (Multiple Regression and Adaptive Power) method for choosing suitable FAT when extracting drainage from DEMs. This work employs 36 sample sub-basins in Hubei (China) province. Firstly, topography, the normalized difference vegetation index (NDVI), and water storage change are used in building multiple regression models to calculate the drainage length. Power functions are fit to calculate the FAT of each sub-basin. Nine randomly chosen regions served as test sub-basins. The results show that: (1) water storage change and NDVI have high correlation with the drainage length, and the coefficient of determination (R2) ranges between 0.85 and 0.87; (2) the drainage length obtained from the Multiple Regression model using water storage change, NDVI, and topography as influence factors is similar to the actual drainage length, featuring a coefficient of determination (R2) equal to 0.714; (3) the MR-AP method calculates suitable FATs for each sub-basin in Hubei province, with a drainage length error equal to 5.13%. Moreover, drainage network extraction by the MR-AP method mainly depends on the water storage change and the NDVI, thus being consistent with the regional water-resources change.

Spatial Difference of Terrestrial Water Storage Change and Lake Water Storage Change in the Inner Tibetan Plateau

Water resources are rich on the Tibetan Plateau, with large amounts of glaciers, lakes, and permafrost. Terrestrial water storage (TWS) on the Tibetan Plateau has experienced a significant change in recent decades. However, there is a lack of research about the spatial difference between TWSC and lake water storage change (LWSC), which is helpful to understand the response of water storage to climate change. In this study, we estimate the change in TWS, lake water storage (LWS), soil moisture, and permafrost, respectively, according to satellite and model data during 2005−2013 in the inner Tibetan Plateau and glacial meltwater from previous literature. The results indicate a sizeable spatial difference between TWSC and LWSC. LWSC was mainly concentrated in the northeastern part (18.71 ± 1.35 Gt, 37.7% of the total) and southeastern part (22.68 ± 1.63 Gt, 45.6% of the total), but the increased TWS was mainly in the northeastern region (region B, 18.96 ± 1.26 Gt, 57%). Based on mass balance, LWSC was the primary cause of TWSC for the entire inner Tibetan Plateau. However, the TWS of the southeastern part increased by 3.97 ± 2.5 Gt, but LWS had increased by 22.68 ± 1.63 Gt, and groundwater had lost 16.91 ± 7.26 Gt. The increased TWS in the northeastern region was equivalent to the increased LWS, and groundwater had increased by 4.47 ± 4.87 Gt. Still, LWS only increased by 2.89 ± 0.21 Gt in the central part, and the increase in groundwater was the primary cause of TWSC. These results suggest that the primary cause of increased TWS shows a sizeable spatial difference. According to the water balance, an increase in precipitation was the primary cause of lake expansion for the entire inner Tibetan Plateau, which contributed 73% (36.28 Gt) to lake expansion (49.69 ± 3.58 Gt), and both glacial meltwater and permafrost degradation was 13.5%.