Search

This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes. Plain Language Summary: This paper presents a data‐driven method to improve rainfall‐runoff models used to generate future water resources scenario in climate change studies. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to monthly streamflow simulations over a large data set of catchments in South‐East Australia. Our results show that DAISI improves model performance for a wide range of metrics and increases the sensitivity of the model to climate inputs, which is critical in climate change scenarios. Finally, the improvements identified by DAISI take a simple mathematical form with distinct regional patterns in three sub‐regions of the study domain (Western Victoria, central region, and Northern New South Wales). Several improvements of DAISI are discussed including the inclusion of additional observed variables such as evapotranspiration to better constrain model simulations. Key Points: Data Assimilation Informed model Structure Improvement method diagnoses hydrological model structures by combining data assimilation with a polynomial update of state equationsThe method was applied to the GR2M rainfall‐runoff model with significantly improved streamflow simulations in 201 Australian catchmentsThe method identified updates to state equations with marked regional characteristics that could guide future improvement of GR2M [ABSTRACT FROM AUTHOR]

Mountain glaciers are considered natural indicators of warming and a device for climatic change. In addition, it is also a solid reservoir of freshwater resources. Along with climate change, clarifying the dynamic changes of glacier in the Aksu River Basin (ARB) are important for hydrological processes. The study examined the variations in glacier area, elevation, and their reaction to climate change in the ARB between 1990 and 2022. The glacier melt on the runoff is explored from 2003 to 2020. This investigation utilized Landsat and Sentinal-2 images, ICESat, CryoSat, meteorological and hydrological data. The findings suggest that: (1) The glacier area in the ARB retreated by 309.40 km2 (9.37%, 0.29%·a−1) from 1990 to 2022. From 2003 to 2021, the ARB glacier surface elevation retreat rate of 0.38 ± 0.12 m·a−1 (0.32 ± 0.10 m w.e.a−1). Comparison with 2003–2009, the retreat rate is faster from 2010 to 2021. (2) From 1990 to 2022, the Toxkan and the Kumalak River Basin's glacier area decreases between 61.28 km2 (0.28%·a−1) and 248.13 km2 (0.30%·a−1). Additionally, the rate of glacier surface elevation declined by −0.34 ± 0.11 m·a−1, −0.42 ± 0.14 m·a−1 from 2003 to 2021. (3) The mass balance sensitivities to cold season precipitation and ablation-phase accumulated temperatures are +0.27 ± 0.08 m w.e.a−1(10%)−1 and −0.33 ± 0.10 m w.e.a−1 °C−1, respectively. The mass loss is (962.55 ± 0.57) × 106 m3 w.e.a−1, (1087.50 ± 0.68) × 106 m3 w.e.a−1 during 2003–2009, 2010–2021 respectively. Warmer ablation-phase accumulated temperatures dominate glacier retreat in the ARB. (4) Glacier meltwater accounted for 34.57% and 41.56% of the Aksu River's runoff during the ablation-phase of 2003–2009 and 2010–2020, respectively. The research has important implications for maintaining the stability of water resource systems based on glacier meltwater. [ABSTRACT FROM AUTHOR]

The impacts of the accelerated glacier retreat in recent decades on glacier runoff changes are still unknown in most Andean catchments, increasing uncertainties in estimating water availability. This particularly affects the outer tropics and Dry Andes, heavily impacted by prolonged droughts. Current global estimates overlook climatic and morphometric disparities, which significantly influence model parameters, among Andean glaciers. Meanwhile, local studies have used different approaches to estimate glacier runoff in a few catchments. Improving 21st-century glacier runoff projections relies on calibrating and validating models using corrected historical climate inputs and calibrated parameters across diverse glaciological zones. Here, we simulate glacier evolution and related runoff changes between the periods 2000–2009 and 2010–2019 across 786 Andean catchments (11 282 km2 of glacierized area, 11° N to 55° S) using the Open Global Glacier Model (OGGM). TerraClimate atmospheric variables were corrected using in situ data, getting a mean temperature bias by up to 2.1 °C and enhanced monthly precipitation. Glacier mass balance and volume were calibrated, where melt factor and the Glen A parameter exhibited significant alignment with varying environmental conditions. Simulation outcomes were validated against in situ data in three documented catchments (with a glacierized area > 8 %) and monitored glaciers. Our results at the Andes scale reveal an average reduction of 8.3 % in glacier volume and a decrease of 2.2 % in surface area between the periods 2000–2009 and 2010–2019. Comparing these two periods, glacier and climate variations have led to a 12 % increase in mean annual glacier melt (86.5 m3s-1) and a decrease in rainfall on glaciers of - 2 % (- 7.6 m3s-1) across the Andes, with both variables comprising the glacier runoff. We confirmed the utility of our corrected regional simulations of glacier runoff contribution at the catchment scale, where our estimations align with previous studies (e.g., Maipo 34° S, Chile) as well as provide new insights on the seasonal glaciers' largest contribution (e.g., La Paz 16° S, Bolivia) and new estimates of glacier runoff contribution (e.g., Baker 47° S, Chile). [ABSTRACT FROM AUTHOR]