@article{vinnarasi_dhanya_kumar_2023, title={Tracing Time-varying Characteristics of Meteorological Drought through Nonstationary Joint Deficit Index}, volume={3}, url={http://dx.doi.org/10.1175/jcli-d-22-0437.1}, DOI={10.1175/jcli-d-22-0437.1}, abstractNote={
Standardized Precipitation Index (SPI) is one of the frequently used meteorological drought indices. However, the time-varying characteristics observed in the historical precipitation data questions the reliability of SPI and motivated the development of nonstationary SPI. To overcome some of the limitations in the existing nonstationary drought indices, a new framework for drought index is proposed, incorporating the temporal dynamics in the precipitation. The proposed drought index is developed by coupling the Joint Deficit Index with the extended Time Sliding Window based Nonstationary Modelling (TSW-NSM). The proposed Nonstationary Joint Deficit Index (NJDI) detects the signature of non-stationarity in the distribution parameter and models both long-term (i.e., trend) and short-term (i.e., step-change) temporal dynamics of distribution parameters. The efficacy of NJDI is demonstrated by employing it to identify the meteorological drought-prone areas over India. The changes observed in the distribution parameter of rainfall series reveal an increasing number of dry days in recent decades all over India, except the northeast. Comparison of NJDI and stationary Joint Deficit Index (JDI) reveals that JDI overestimates drought when frequent severe dry events are clustered and underestimates when these events are scattered, which indicates that the traditional index is biased towards the lowest magnitude of precipitation while classifying the drought. Moreover, NJDI could closely capture historical droughts and their spatial variations, thereby reflecting the temporal dynamics of rainfall series and the changes in the pattern of dry events over India. NJDI proves to be a potentially reliable index for drought monitoring in a nonstationary climate.}, journal={Journal of Climate}, publisher={American Meteorological Society}, author={Vinnarasi, R. and Dhanya, C.T. and Kumar, Hemant}, year={2023}, month={Mar}, pages={1–31} }
 @article{kumar_zhu_sankarasubramanian_2023, title={Understanding the Food-Energy-Water Nexus in Mixed Irrigation Regimes Using a Regional Hydroeconomic Optimization Modeling Framework}, volume={59}, ISSN={["1944-7973"]}, url={https://doi.org/10.1029/2022WR033691}, DOI={10.1029/2022WR033691}, abstractNote={Understanding the nexus between food, energy, and water systems (FEW) is critical for basins with intensive agricultural water use as they face significant challenges under changing climate and regional development. We investigate the food, energy, and water nexus through a regional hydroeconomic optimization (RHEO) modeling framework. The crop production in RHEO is estimated through a hierarchical regression model developed using a biophysical model, AquaCropOS, forced with daily climatic inputs. Incorporating the hierarchical model within the RHEO also reduces the computation time by enabling parallel programming within the AquaCropOS and facilitates mixed irrigation—rainfed, fully irrigated and deficit irrigation—strategies. To demonstrate the RHEO framework, we considered a groundwater‐dominated basin, South Flint River Basin, Georgia, for developing mixed irrigation strategies over 31 years. Our analyses show that optimal deficit irrigation is economically better than full irrigation, which increases the groundwater pumping cost. Thus, considering deficit irrigation in a groundwater‐dominated basin reduces the water, carbon, and energy footprints, thereby reducing FEW vulnerability. The RHEO also could be employed for analyzing FEW nexus under potential climate change and future regional development scenarios.}, number={6}, journal={WATER RESOURCES RESEARCH}, author={Kumar, Hemant and Zhu, Tingju and Sankarasubramanian, A.}, year={2023}, month={Jun} }
 @article{ruhi_hwang_devineni_mukhopadhyay_kumar_comte_worland_sankarasubramanian_2022, title={How Does Flow Alteration Propagate Across a Large, Highly Regulated Basin? Dam Attributes, Network Context, and Implications for Biodiversity}, url={https://doi.org/10.1029/2021EF002490}, DOI={10.1029/2021EF002490}, abstractNote={Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.}, journal={Earth's Future}, author={Ruhi, Albert and Hwang, Jeongwoo and Devineni, Naresh and Mukhopadhyay, Sudarshana and Kumar, Hemant and Comte, Lise and Worland, Scott and Sankarasubramanian, A.}, year={2022}, month={Jun} }
 @article{kumar_hwang_devineni_sankarasubramanian_2021, title={Dynamic Flow Alteration Index for Complex River Networks With Cascading Reservoir Systems}, volume={58}, ISSN={0043-1397 1944-7973}, url={http://dx.doi.org/10.1029/2021WR030491}, DOI={10.1029/2021WR030491}, abstractNote={Large dams degrade the river’s health by heavily regulating the natural flows. Despite a long history of research on flow regulation due to dams, most studies focused only on the impact of a single dam and ignored the combined impact of flow regulation on a river network. We propose a new Dynamic Flow Alteration Index (DFAI) to quantify the local and cumulative degree of regulation by comparing the observed controlled flows with the naturalized flows based on a moving time horizon for the highly regulated Colorado River Basin. The proposed DFAI matches closely to dam’s localized regulation for headwater gages and starts to diverge as we move downstream due to increase in cumulative impact of the dams. DFAI considers the impact of dam operations on flow characteristics such as shifting of peak flow occurrence and dampening of peak flows. DFAI estimates the degree of regulation to be small for upstream dams and finds the maximum network regulation to be 2.52 years at Glen Canyon reservoir. DFAI also successfully captures the reduction in cumulative regulation when dam operations (e.g., Hoover Dam) bring the altered flow in synchronization with natural regime due to downstream flow requirements. The impact of San Juan River Basin Recovery Implementation Program is also captured by DFAI as the reduction in network regulation drops by 1.5 years for Navajo Dam. Our findings using DFAI suggest the need to develop naturalized flows for major river basins to quantify the flow alteration under continually changing climate and human influences.}, number={1}, journal={Water Resources Research}, publisher={American Geophysical Union (AGU)}, author={Kumar, Hemant and Hwang, Jeongwoo and Devineni, Naresh and Sankarasubramanian, A.}, year={2021}, month={Dec} }
 @article{hwang_kumar_ruhi_sankarasubramanian_devineni_2021, title={Quantifying Dam‐Induced Fluctuations in Streamflow Frequencies Across the Colorado River Basin}, volume={57}, ISSN={0043-1397 1944-7973}, url={http://dx.doi.org/10.1029/2021WR029753}, DOI={10.1029/2021WR029753}, abstractNote={Periodic fluctuations in natural streamflow are a major driver of river ecosystem dynamics and water resource management. However, most U.S. rivers are impacted both by long‐term hydroclimatic trends and dams that alter flow variability. Despite these impacts, it remains largely unexplored how dams affect the dominant frequencies of natural streamflow over a highly regulated river network. We investigated the entire Colorado River Basin (CRB) to understand how the annual (10–14 months) and multi‐annual (24–60 months) frequencies in natural flow regimes have been progressively altered by dams. Given the significant alteration over the CRB, we captured changes in streamflow frequencies between naturalized and observed monthly flows via wavelet analysis. Based on the similarity of changes in streamflow frequencies (annual and multi‐annual) over the last 30 years, sections of the riverine network were classified into four groups. The annual frequency was relatively well preserved downstream of Hoover Dam, while showing a systematic trend of alteration downstream of Glen Canyon Dam until Hoover Dam. Meanwhile, the multi‐annual frequency component was highly altered for the entire Lower Colorado main stem (i.e., downstream of Glen Canyon). We also identified dams with significant impacts on streamflow frequency by comparing wavelet coherence estimates. This study advances the notion that dams fundamentally alter river flow regimes across multiple frequencies and with varying amplitudes over time and space, with alteration propagating – or being dampened – by both hydroclimatic fluctuations and water resource management.}, number={10}, journal={Water Resources Research}, publisher={American Geophysical Union (AGU)}, author={Hwang, Jeongwoo and Kumar, Hemant and Ruhi, Albert and Sankarasubramanian, Arumugam and Devineni, Naresh}, year={2021}, month={Oct}, pages={e2021WR029753} }